{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.Strategy Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "strategy_name_list = ['boll_cross', 'sma_cross','sma_cross_add_trail','strategy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 获取每个策略回测的结果\n",
    "result_df_list = [pd.read_csv('./backtesting_csv_result/%s.csv' % st_name ,header=1) for st_name in strategy_name_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 分析每个策略之间回测相关性\n",
    "drawdown_list = [df['drawdown'] for df in result_df_list]\n",
    "dd_corr_list = [[drawdown_list[level_2].corr(drawdown_list[ind]) for ind in range(len(strategy_name_list))] for level_2 in range(len(strategy_name_list))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>boll_cross</th>\n",
       "      <th>sma_cross</th>\n",
       "      <th>sma_cross_add_trail</th>\n",
       "      <th>strategy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>boll_cross</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.744660</td>\n",
       "      <td>0.305044</td>\n",
       "      <td>-0.162440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sma_cross</th>\n",
       "      <td>0.744660</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.226181</td>\n",
       "      <td>-0.179857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sma_cross_add_trail</th>\n",
       "      <td>0.305044</td>\n",
       "      <td>0.226181</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.111666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strategy</th>\n",
       "      <td>-0.162440</td>\n",
       "      <td>-0.179857</td>\n",
       "      <td>0.111666</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     boll_cross  sma_cross  sma_cross_add_trail  strategy\n",
       "boll_cross             1.000000   0.744660             0.305044 -0.162440\n",
       "sma_cross              0.744660   1.000000             0.226181 -0.179857\n",
       "sma_cross_add_trail    0.305044   0.226181             1.000000  0.111666\n",
       "strategy              -0.162440  -0.179857             0.111666  1.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data=dd_corr_list, index=strategy_name_list, columns=strategy_name_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 分析每个 策略之间daily return的相关性\n",
    "daily_return_list = [df['timereturn'] for df in result_df_list]\n",
    "return_corr_list = [[daily_return_list[level_2].corr(daily_return_list[ind]) for ind in range(len(strategy_name_list))] for level_2 in range(len(strategy_name_list))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>boll_cross</th>\n",
       "      <th>sma_cross</th>\n",
       "      <th>sma_cross_add_trail</th>\n",
       "      <th>strategy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>boll_cross</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.833342</td>\n",
       "      <td>0.652789</td>\n",
       "      <td>-0.006778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sma_cross</th>\n",
       "      <td>0.833342</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.745092</td>\n",
       "      <td>0.003031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sma_cross_add_trail</th>\n",
       "      <td>0.652789</td>\n",
       "      <td>0.745092</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.002250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strategy</th>\n",
       "      <td>-0.006778</td>\n",
       "      <td>0.003031</td>\n",
       "      <td>-0.002250</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     boll_cross  sma_cross  sma_cross_add_trail  strategy\n",
       "boll_cross             1.000000   0.833342             0.652789 -0.006778\n",
       "sma_cross              0.833342   1.000000             0.745092  0.003031\n",
       "sma_cross_add_trail    0.652789   0.745092             1.000000 -0.002250\n",
       "strategy              -0.006778   0.003031            -0.002250  1.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data=return_corr_list, index=strategy_name_list, columns=strategy_name_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## １.单策略绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "st_name = 'strategy'\n",
    "st_result = pd.read_csv('./backtesting_csv_result/%s.csv' % st_name ,header=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xa6cfe80>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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pj+vhrcmSFkkKBrOfeOaE+rI2N3Wb0A61/KiYYMDoWHfm4vtYd39ewGdh6mJf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\nmPgBZdZOqLAXxFUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaeab240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "st_result['value'].plot(figsize=(19, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xb114d30>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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I1k1Lxafu3h34Wx/KNjEzj9mGjZm51qFv/sWqbNqlgi+WAKa1oXeN1Aq3SuNn\nyj4OEWUtyew2AsAnAWyTUn5Iu1+fZ+yXADyWfvOoCqo63EZlFujb862th3DzD3f1tT3t7qPOeFMA\n97kdREWz5/ikd3t0KHjNRUqJO7eP590kWqBsW6IWnIUW569cZFx2dND5ru45UfxpgE31OIBgv0MN\nvbls7eLW52dcuNXWMklOT8979893ESC95cH9+Km/3RQYthOVScLhNkSUtSSZJC8C8AYAjwohtrj3\n/SmA1wshroNz7vAMgLdn0kIqvd3HJgNFw/SDtZdtUuIzUL2z8rtffAgA8Nb/dGHu7fCH22gFcUv8\nvvbbkTMzWDU2xEwSoghxNR2GB2oYG06UrErUM1tK1CwR+E4O1YPXAVXA+8LVY87fJd6p65kkDXdY\n2/JQNhfgB42yumCi+j96zOJZKxZ1NQXwB763HYfPzGB8YhYXuEHXyMKt3TU3NVJKfPjOnXjJpatx\n3YZlfW4NEWWhbQ9GSnkXzPsjTvlLsVQF+enQ7Adl7pjo/OE2hgwOKSOvAGXWHvdfwSmAe/bdxw7j\nHZ9/EO/4yYu0e6vxvSVKS1yQ5PJ1i7HjyNnIx4nS1HSPuZet8bMpVi8ewlOG72DNyrZORxYGa1ag\nzoceJFG3TYVbRcbDbaQ33MZ/7RWjgz0VxdVrxUQWbu1zoZJjZ+fwwdufwte3HMCdf/BTfW0LEWWj\no9ltiDox4BZHCx+4i1bDo1tqM0zbk1bRsm7o43cr8lb35PDpGdzz9LGOnvOOzz8IALjt8cNeJ/Br\nDx3AvhKkZxP1opMrwHfvjP5dCSFKdRJK5WbbEjUhsGjQn3p22YiTWbF80QAAv2BrzT3r7uNhOpHf\n+MR9OHBqGgBw3vJg7ZRgJolzu2ac3ca5r5vMjiT04TbKUN3Cln2n8I1HDna0LjVT4Fc27/OOuxLm\noTX6Pf2oc3d62imge/j0TO6vTUT5YJCEMidl8CqGXpW9zBkPXiaJ4QC9/+R0zq0JZuhwCmDfWz+7\nGb9+8/2YbbQWtWunXhNeoGm2YeMPb3kk3cYRFch3HzuMS//sO3hk36lEyy+OGU5jCcEhapQbWzpB\ngsDsbu7e+23/6SL83k2X4BVXrwUAWG7Pt+hF5O/eedy7Hb7wovej7ARBknuePt7yWBr0wq3K8IAT\nqPq9f3m4o3WpC2ufuGu3FxyypTTWJNE/534EY+/d5UzFPDbEIYVEVcUgCWUm6ri1vzJX41sLtyr9\nuLqgD7ejcgO7AAAgAElEQVTx7uNZCh49cBpA8MpbUnXLCny+jx04k1q7iIpm05PjkBJ44lCy73nc\n7sUS5RrOQOXWtGXLUNPnbFgOALhuwzK862WXYvGwk1FSd6Mk4Wl0iyw8XfGbP/0A9p2Ywqbt416R\nVNNwm5rlZNcsGxnIpF3qsCqEwICbCXKRW/OlU3r71cxYkTVJtLv6EetSgakrz12S/4sTUS4YAqXc\nTcw02i9UIqYDdD/6XvprljlDJyvdfCYDdYvvKy0YndYviAuCWEJUZmglFZ8tneE2+tCMN75wI372\nqjV41orgLDcqk6RRoi/o+MRsy32//69b8OCek/jL11wNAKhZ5uuel5wz1lONkDhSy/T4l7e+AAdO\nTWNLwky0sHrNb7/at/zwqaNYagjwBIbb9KHDpYYvhYsDE1F18NdNmYmqpm66t4xT1ZoKt2ZdST6J\nYLoxKd28F4uH6oHnMUZCVdbp/ituKSG6y94i6oaa3UYPZNctgfNXjrZkIqiaJEUfbtPOg3tOAoA3\n9a4pkwQAhuq1roabJuEMh3Fe94aNK/Dq69Z3va4LV416t9Uns3rxkLlwa5+H26gAmx7YIaJq4a+b\nMhfucFclBdsr3Kp1tPo79W413tesdDL0SF25etbKRYHPst8V9Ymy1eGU7LHDbQSH+1FumrZzgUDf\nRUftr1XtjqoE8c7OOtm5Uds7NGBFZpLc/MNdeNH77mwZzpOULc2FVbuh1/dQuw4pJa5ev7Rl2X4P\nt2m4mSRRgSkiKj8Ot6HMhfvJese5zH1otR36AVoIAUjZl0CQeklhuI86CyGpAnK2HZx+MK3OIFER\n+Zkk7U3MzONbjx6KfLzG4TaUIyeTBEiS72eVcArgOGfdIcxRJ+yDNQsP7zUPgXnvt7cBACZnGxis\nD3b82nbEFL3dsAN9Q3d2m4ggjJ4d1I9gl6oDU2OfgKiymElCmdH7H1G3y8yfArh1g/qxiXrhVtHJ\n2c4CkfR7J6XEGTd9uWnLYCYJ+0NUYd7XO8GP5T+2H4193LKqcxJKxefXJGm/rD8FcDW+n5+/fw8A\n8+w2gD80JC6zq9t3IiqI0Q3941A3m1Gz2wTa0I/hNgWfP5qIesYgCeUucCCsQCc6UNjTu7MfLVFt\naJ0AeNOT49h19Gxf2lMYCT+Tf/rhLm+6xXCQxFRln6gq1Nc7ybljuwCIYCYJ5ciZ3UYk2kd7w20K\n3P+Iq5dy9frgjCpqMzaECtQqP3G+M8tP3O+x24CmbZuDGN3Q+4OqPXrNE51+X14FeG9/4gi+/MA+\n5zWbxf3uEFE6GCShzMjQv4ox86KExxvVZv1qlH+Skd8GnZ1t4LuPHTYetCUkpJR48z8/gDd9+oHc\n2lRESYtRfnPrQe92U8rA8xgioSpTJx4/3n2i7bL1iJk0/HVVIwhO5WDbTuHWJCfsVgkKt8ad+JuC\nBsMDFtYvGzEur4JCcdkP3f5U06xJEhxu495nRw238W9vPzyRyuu389bPbsYffXUrAH+a9OJ+g4io\nVwySUOakDJ6gmg4qTx3J5yCXJqld6VBEp4UPU/CRTTvxjs8/iHuePua0QQQ7EKote09M5deoAkr6\nmQzXa97t1kySlBtFVEDDA7W2y7Q7GXWmAOYpBOVjcq7pzG6TIJStgga7jxX3mDg9Fz0bzf6T0y33\nxf1mkxSq7TagmW5NEr096t/2w21U4dq8zMw3MTvvBJwYCCaqLgZJKDuq8FYoLBIo3Or+m1e6ZJr8\nmiTRj+VBDaOZcIu3hQu3lu+d7a+hAX+3aEsZSMlm4VaqMpVB0kww3r7dUAWLw20oJ4dOO0GDydlG\nohN2ddJ9cmouw1b15uljweGxV67zh9jos8AoL79ybeS66l4mSRY1SWRqs77pQVV/uI35uKu/5tRc\nvkGSv//+Dq+jxV0cUXUxSELZCx1FTFcXH957Cg/uaZ/iXSjuZjy896R/nzpw9vHqghDBQAmv5jqS\nvgtDWibJvU8fx492HPP+VlMDE1XRilFndoskw+3bFb0UgvseysexCSfY8ZJLVicKkgghcOmaschC\np0Wg/3RuOH85vv3Ol3h/jw3VW7ZzZLB9Jknc8KJuf6tnZ5st67187eKO1jE118Cf3/oYdh2dNLar\nzcg+3L3zeEev163L1jjbNT3XCMy+Q0TVxCAJZUY/diSZ6eb1N9+feZuyUK/5vRV1qx9XUDcbgkwS\nPFFRkgau1iwZ9m6PDdexctSfFnHt0mHTU4gqQQU+kmSStCtcaAnBEwjKxbbDTn2I5YsGEmf77T0x\nhdufOJJbPYvORf94albrb+vZ5y2NXD5RJkmXv9WH9p7EbCO4v/jVn9iAtUuGcd2GZYnWcf/uE/jM\nvXu8Oh96e2xpLpiuf84DtXyCXU0tu4VZckTVxyAJZa61cKt5ublGuaZUU5tR0w7W/s38j6D+1ZRg\nhX+eqDiSvg2rxpygyGuvXw/bLudQMKJumIpRR1HLbFy5CG+88fyWxy1mklBOjk7MAgCetXJR4voY\nM25NCb1Qd5GYfjqrxoYAAH/48staHqvXorvzVoKaJN3+VleMDuLcUMFYyxK4bO3ixBcmTMsFZ7dp\nfY7+Oec104x6/ySkdpuIqqp1YCNRSvTCW7pABfM8G5QyL91Su68fhVvDgkVbJYMkrqTvg5TOCV7d\ncgpPzjf94N1/bD+KpjuLAlHVqCuliYIk7rJfetuNxgwrFm6lvKjhHqvGhrzaXEkVdVr3QL/CbeL3\n3/WfAADLFg22LD8Yk01RT1S4tfM2Os+TOG9566w6NUvgkf2nu1sp9JpvUVMA+7eT7K/SoF7Hllr/\nj/s4ospiJgllTiI89KYaBxXTVvhTAOfalGAbEAyU8ETFkXQKYAkJIQRqlkDDlpgPZTglmR6VqIzs\nDoIkKsMqKmAoWLiVcqK+ZzWRZG6boKLGu02H7WWLBo0BEiB+Su6a+1gWQZKo4TCDbmbLnuOtdUbC\nTJ+aN3ugbQ6S6JnHeWV7etkjUnrfOe7iiKqLQRLKjDopDR98q3LO7mfKGB4ryKEzHKDKmm1LPH30\nbDEDYR00ScC9Em5LzIVSeRsJ6jUQlZG6Ip/kpOMx9ypxPeIs0xLOiczPfOgHOD01n14jiUJUcE+I\nzjNDijpjWafH0IF6dHdebeHNP9oV/Xpd9hSipuh9zXPWAwC2aXVGIhmeb2v9K9NndHzSn5ko70wS\nKbXXLGBXh4jSwSAJZS6uJkkhT6YTkFJier7p3Na2UHiP59eW8FUYoV1NkzLfTJIvb96Hmz74A9z5\n5Hhur5lU0ndBvV11N5MkPL3gQMzYb6IyU/vmJPsMFUhZEjHjk9o/7hw/i70nptJpIJGBLaUXIOk0\n5lHUTJKkVi926pQMxGzIInfmmy89sC9ymV4ySUxBjPNXLkq8XnPL42uSqJoyQH4XLhq23yZm6BJV\nH3v7lAs9GFKFg8snfrTbeL+6itXPLRROQ7y/ZY6JD6o6/b4CnhQlrkkC5+2zLIHT0/OYmmtm2i6i\nolD75iSFEKfnG7j4nOhpVNV0mQDwax+/N50GEhnYUnoF1DvNDClDTZIVo+YhNgBw0+XnAIge9gYA\nP3vVWgDAT1+2OnKZbvtl7QqrJlmr6TPQZ7exDC8wM+8fl/PKJPGLyWqZxNoWnpqaw/+9Ywc+e+8z\n+J+3bC3tRUAicrBwK2UmqnBrFQ4b33v8sHdb3zw/gyN+K89bPoL9J6czaFmocKv7v7wVsePZyfsg\nICKHERBVVVO7UtrO1FzTu0JtslTLMGGgkbKkZzN0utcu4KEKgN+vuHztYvzhyy+PXO4PX34Zrl6/\nFNefvzxymZolcOmasdgAUre9hKiaJJ0Usdeffdmaxdh+ZCKQ1WZqtr5/yasmyQl3iI+UfuFqffu+\n+OO9+NDtT3l//9Vrr0FOsxMTUQYYJKHMhQ9fVYiuD2rjf01b024T1y9zgiQXrR5Nt2Eu/bjM4omO\nTma3AcxXrzpZD1HZqO/2A8+cbLvsD546iudtXBH5OGeAorzsPT7lnbR2mklS2Jokbs/iz3/hKlx8\nzljL4195x42YmW9i5dgQfvMF5ydbZ8yxq9t+WVRNEsvLJGm/Xv0jGHEDr1ILQpg+o9/56Yuwbukw\nvvHIwVwyScbPzHi3pTbcRn/bwjMrcSY8onJjkIQyI7Ub+iHMrsBZ+1BUkbSEHQMZ+jdNgf5EzjVJ\nihxA6KhpAl76NtFCoU40k3TsB2sW5prRY/l4ckB5GJ+YwbcePeT93eluu7D7efeAFdW858YEKE3a\nzfsTd+y+5cH9EAB++SfOa3ksaorebmf6Gx1ygyTu382IIMw5i4fx9p+8CHdsG8f4mdnOXqQLeqFY\nW0rjcJtwM6swtJxoIWOQhDIXDhjof5X1GDJU99PMTcNt2tYRyzBKIhAsXpfne6w+6yL2O5NeKVPb\nEDXcpigzFxGlTXXqk5w4WkLghpgUfz0Ta93S4d4bR2QQvnqvvrrtvsIjAzVMzzcLeawC/K5Bms2L\nO3bFBTP+x1ceARAVJInKxlHDbRJkkmhbqfpOTiBCOtkYMR/SxGwD249MtH2NXu066k9lLJEsAJJX\nrRQiygYLt1Jmoo4hVThurFniVJR3TqS1KwkJC7d60yNn0bhATZJ8hzeplypKv1Pf9sRvg3SnAOaV\ncFpg/CmA21d7tqWM/Y3oQca8agYQqWNwu2E0n/kvz8ujOV3zjqUpRXHarabb4H9UzZBum/3cC1ao\nBuGZ404B+InZRuTyl60Zi62NlBZ9hi5bBqcDVsLbzEwSonJjkIQyJ2XwQBI4cS3pVfmx4TrqlsCv\nPXdD4H6vonubg2NUUdu0BK7MlPMt7ishYmb44PtJFeUXSzQPizw6MYt3/esW7DsxFZlmr+hXf6sw\nxJKKKXwIVbG5dufoV567xPj8osgiKzNuW6PiorON+KLLUTVDhPZ423ZpB9XBmn+hadot+Pz8C6KH\nFq0YHcplyFTDHVp4/spFoeE2vvCQppxmJiaijHC4DWXGy5YIHSSL2inphJ5iap7dJv75mdYk0V9H\nljcQlbZOpgAGYCyWR1Rlenp4U0pYoU7/dx87hK89fACrFw+1TYPXs0yaVdjpU0EFv1vqRLVddoH6\nehb1u5lFVmbclkb1E/RhJiZRUwB7/aMO+x8DNctbr8rEiAvGCpFPxsZc04YQboacVust7qWL+t0i\nomQYJKHMhQ+SEzPz/mMlPYaoFFMhIma3SdgxyGL7hfBrkkjIXDNJvJcqyEDvQAZT4s9EQkBgxeig\n+fE0GkZUQHpmW9OWGAidZ8652VVzTdsNFEevSy/c2ozKyiLqUfgYunx0AD9x/nL81o3nxz5PnXgX\nfUhEWofSdsN2oodHx78/bQu3Jsim0F9CBUmkNqQlrgh0cMBzduaaNgZrFmqWgC2lNoTQf/VwM4v+\n3SKieBxuQ9nxhpRofwD45F27+9KcNEnpdAIERODEQhiyS8zPVzVJ0j+ICoSmAO5DqnsxQiTd864Y\nGbDfQ1U037Rx8LQ/zWVcHZF202QDoSAJfzSUk6F6DV/9ry/Eq69bH7ucFyQp6FCwLFrVmtXbvmZX\nu5+ubZsDMCqjJ8l26MsM1P1MEm9a55j9jGWJXI7Jcw0bg3ULAgIz800cnQjOqPPgnpP4ty0HA/cV\n9btFRMkwSEK5m5yLH+NaBtK9ehLuG6g/73xyPLbeiHcNIuNj6EI/N9E3P/FwG3e5eo27R1o4TmpT\nXALm7A8vuJtgFhz9Mc7yQFnp9pulgnhF/Wr6/YeUCrcaX8O/HZX10O63KyOG2yStzxZeRq9JooIM\ncfsZgXwyNsYnZjFQsyAEcHo6mA0917Dxyx+7J1DcFWBwmKjseBZAmdMPExtWjGCgJoyPlUmgJol2\nvzqW3/bEEWzeczLy+erYuf/kdOpXG0YGa4HgTZ4pn0XuE3TSNIHoFF/WeKEqmnKD19duWAYgfoab\nA6emAXSQSVLUM1EqvW6POerr+aHbn8p1BrikvBBJqmmZwe3U+wZR70D74TbxNUM6fWfVcBskHG6D\niCHPaXv8wGnMzDdhCRHIspOI3r9xv0dUbgySUGb0bAm/CFnZB2I4vJokiO6kTcdkzOhPmZ5PN7Pm\nglWjgdfpx3G6ICVJApJ2hNVSejDvz151Bd7/y9dk0CqiYjjrTrO5ZNgpVWbq4Kuf0Pe3jQOIPzka\nHvC7F5wCmLpxcnIOU3PR078C3Qet9SEiU0XMbk25cKvpp6r/LKOCIe1+us5U4K33ewHUBB9PYLhN\nzTDcJq5AdFRhuJSNDddx8TljEAKY17LspJSR38ECxt6IqAMMklAO9Jod4emA+9CcHp2dbWBipuEO\ntwkfvBN2abQNTzvTwxIiEIxK6yrZH391K971r1vaLFWsD1QmuFLW+hynA13Xen7nLV+Ei1aPeY8T\nVc3mZ04AABa7QRLTieNDe4PZcXEXeC9aPYaP/sb1XgHNw1q9E6IkXvz+O/HrN9+f2frXLxsBUMwg\niT8FcHpXHMLHrkAmSdeFW6NqkiR7vvPi/s1BtybJ3hNTXtHXdoVb88iWbdrAOYuHnUySpp9lJxH9\n3n31of2Zt4uIssMgCWXGH7/u31fABIOOvfrDd+GWB/cbx9zqfYW4w7b+WJLq753Qx+9KKfHeb23r\neZ2Tsw186YF9+NrDBxItX8SMoU76UQJAXcskUTMZEVWVqsFzxdolAIAd42dbllEnMErsyYsQeOU1\n63DjhSsBAJu2j6fVVFogJuea2LLvVOwyar9+w/nLO17/7//MJQDisz77Je0pgE3Hr+AFq4hMkl5r\nkiRtoEt9jt959LCXSRJXHiynRBLYtkTNcgLD881gpy0qSPP339/RsiwRlQeDJJQLf3ytKFiuQeee\nPjoJIKImiXY7tnBrgjTXbgkr2JA7nuz95OTwGf8qcNxBv2hZFjLmr+jnOMvps9sEPteeW0VUPOp7\nfdV6J0jSrtAj4A/RifPCi1YBAPafnGqzJFHn1HfyLS+5oOPnDrtzXD9+8HSaTUqFFyRJMTgfPnbp\nfY89x82/z3bDbY5PzpmnAFaz2yRKJPEXWjk2hMVDdZyZmUfTvYJUM43n0V4nj5oyTSmdoLAQoeE2\n8X0CTgNMVF4MklBm1LEhHERQB7SmLfHw3ujipkVnGbILRofq3u34TBL/0bQroFuBTBJgxeggAGDR\nYK3rdepN/MUP3912+SJmXXT0NgvgXDcVG1DpxAXcKKK0hMb/mzr34XvmGu2vki5dNIDBmlXYWUSo\n3Pxjaef750vWOEMoz8zMt1kyf/5WpTW7Tet69N94VMAz7iRfzfKiz/bivZ6XSdL+hx9+iRde7GSf\nqesxcbPbWDllkjRtiZplwRLBotZxw23Q5jEiKjYGSShzgSi/dqz7xiMHcNsTR/JvUEq8ToU+nrZm\nYfXiobbPzTKTpCaC3aFrz1sKALh6/dIe1uq3cduhM9FLFbhD8J5/fzzhdITOv+oqI5A8Q4iorNS3\nOm5q1PC+KkmQBHBOmNKexYtI101g/pzFwwCKWZNESTWTRPv9zjVs3LrloPf3X37rCRw4NY3Nz5zA\nEwf9Y3xc/2TGLTp/7XnLWh5T7e7mZ28J4RRudZ8ck0gCCJFLv6NpS9TcYv3BKYDjU0mYSUJUXgyS\nUGak9q8+vlbdv+/EdP6NStHMvO2keoburyUYjPu41gnp9Rga7kSF/27qH0SXkrbRKzbX/UulSm/3\n3TuPYzJhZ7ilHK9A12OsicpA/VZUkMQYDAzdlXS8fc0SPFmgTPTytVLZlUUMkqQdjA/X7rjticP4\ns397zPt7vinx0U078Sv/7168+iN3effHBTnUb9qUpepdqungwoTiBEmAPcedoc3tCrc668h2/9K0\nJSxLYLZhY2Y+uN8zZcucv3IRgP7MLkhE6WCQhDIXSCTRzuCLciLdC2e2Hm18KvwiZkmnJjRNtdkL\nfbjNvhNT3hXcbqdKdJ6b7fJ5SdqRClfrV9M9E1WVOuGpiehMkm73IZYQYP1CylI3++chtxDxphTq\ndqUt7WNo+P05OdU6REZlSOg1N+KCm2ofYaxJ0sFFhfAyQjivOzHjZOuuWzLS+iQEXzvrGKwtJWpC\nBIbhKqbX9jPyitobIqJ2GCShzJhqkuj3F7FuRTvjZ4LTWJo2IcmUfZYA1i5xUn3/7van8I937MBz\n3/t9L321FzVL4Bx33ROzDS8I08uxutMDfVE6BuGTuiTxKFMgJfCZFmPTiFIVziQx/YbDM3G9wZ3e\ntx1LFGefQNXi9yc671AIIWAJYNmigZRb1btMCrfKqD8cpowNfZhc+NjoPWaa3Sb6ZQztCi5kaUNo\napbA0pjPxx/Wk30mSc0SuGDVaOD+qNE2KtgsGRwmKi0GSSgX6mRVPwZ306nptxNTcy33RfU74o7Z\ntvQ7JF95cD8+ePtTODoxi5OG9XdKD8A0mjKVwrDhVfyHO53nbKOJF73vTtz8w12B5Qp7PpSkwwbD\nECaU8/tKlJT6aVgxQRI96Pjun78SF5+zONG6LQ63oYx1u3e+Yt2Sgh6v1NDVlI47oeOX6YKBqUCq\nvtyuY5PGVZsySfwMj87fXBVUbUZML6zzgjEdv0pnbOkMtxkMzUcsISMurPjPI6JyYpCEMqcfQFI7\n4PdJoxk84DnDbdByHxAdKFBXXwZqre/F39++o+c2CiFQd9d9enpeG27TvfC2vOnTDwAAJmYaOHBq\nGu/99rbAaxS1W5C0w9Jak0SbMaiwW0fUPbWfrsWkr+v3xdUJCKsJBkkoG73ujy3RWlesCLKeArhd\nxuSJyTm88h9+hE3b/aFI4UxX9Zs27Qo6KdyqFhkesNz1OfsLW0pjAEZnWdH7qzQ5hVsFBuv+adN5\ny0cgZbK6LURUPgySUGbiOi8ywcGviBp2OEgS3AYJ7QpKxDrUQbNea/35/evmfT23EQAG3HLwf/r1\nR7F5jzPNci+FzaI+y8hVFqRjEG5Gkg6LaRFOAEwLRexwmy6DJII1SSgjvQYTVP2LolEtSqubFF6N\n6cRe/0nvPTGFJw6dwRfv3+s/J/QbtmPee3VBLFFNEnehf3nrC9z1Cdi2c0EpaT8xr+E2epBkZKDm\nDrcxZN1J1a5Mm0VEGWKQhDInpbkjU8IYCZpaL+FCd2xq+ADZbrvUQbPewUlGp+qGLJU0M0n8+4MP\n3LPzGIDidgySNstUuNVbR0G3jagX6nutTkrMv2H/zpOTyYcG1ixOnU3Z6DWYIFDMfbo/I2B6/YRg\nkXnfL1x7LgBgdKju3WcKOoSH7vqZJNFFSTr53Q/Va+76nOfpw5Kj5NWPPDPTQM0S5my6mE187MBp\nHDs7m23jiCgTDJJQZvzCreYoewljJN5wm0++8QZ88/de3NLBklK2nZLOzyRpfQeuWLcklXYOGLJU\nehEZJAn9vXJsyF2+gL1OJMwkMXxfBUTbYVREZaa+93GZJPpd5ywZSrxuZ3Yb/nAoO10HE4o63EbV\nJMmgJMnuY5P4P998wvv7LS++AGND9UCwwzb8XpuhVJK4ormdtTv4WmoK4KYt267Hy1jJ8EPce3wK\ngDPl+TXrl/qvLYRTkyTmuW/+5wdw65aD2TWOiDJTb78IUXqENhSlnJkkzuFwbKiORYN1c1X3NsNt\n/KrtrYGM0cFaGs001jvppRMR1Q0In0g1U6h/kqkk46MNATxnCuASfmGJEgrPbmMKdNpS4ur1S/CB\nX70WlyQs2gq4QRJGFykDvQbkRQrryIKfSZKuW7ccwG1PHAncV7OciwD37jru3WcKaoaHzEkvk6T1\ndTqZmjecaWxZzr5GStk2k8RP5sjuM3xw7wkAwMuuXBOYCcnJkGu/jZecM5ZZ24goOwySUOakBD57\n7zMAggf8Mp50ztutWSCBYmho36lRgYUBw8E/rcO8qd5JNsNtgn+rbStgnxNA8mFALbPbcAZgqjg7\nFCQx/VZUzaXL13aW8WZZxd0nULl5X6suuxMZjnpNRdo1Sd75pS3G15iea2KxNtzGFNQMB078GYAN\nmSTeMkmyN/12OP+6mSQJatd1UiC2W0fOOMNlLlw9FiheW3OzkNoFaM5bPpJd44goMxxuQ5k7O9vA\nv/zYKUjqD1lon0ZZRCrdVGWBCIjWs+Y2wzJU58N0hSStK1rDdcNPu6fCrWbhDpD6uyiF8Loq3Gq4\nTx9uQ1RF3nAbryZJxDDJLn4INQ63oYz0mnEhCjrzUhYtitpMSwg8d+OKwH3hIq0A8O1HD3m355s2\n3va5ze7zW5f1+nodtE8FW1RNkqYdUe/E8Jwss4HUvmvV2CCGB/xsX8ty+n/tXjrt4c9ElA/+cikz\n6qClT5sbLNxavrNOtS2q6KoQoasIUj+om4+c0u18zDRaeyFpZpJ8550vSW3dUR2Q8N1FPxFK0jpn\nm+IKtxZ7G4m64RVudXsFpp+yrdVc6oRlFfNElKqj2/5EcQu3evkVqaxP1c8w8YbYaY+bMkk+d98e\n7/b4xCz2uLU6jDVJOqgVEl5GTQHsDLeJf243wZhOqfoslhBYOTro3e9Nl64taxoyPWi6aEVEhcdf\nLmVO7xzr08KVL0QC7Bg/C8AfbmPaBr9wq3kd6v24fM1iLB4OjnjrtbP2kV+/3rs9NpTeaLqo2Edr\npob5/n4JdwpNxehMWobbpNUgooKLq0kCdJf+bxX0aj0VV/JgdI81SURxjlcmaQ63ic4kaX0f2h0r\n9cfjMkne/90n8Ykf7YpdV7hIrV64tf1wG3d/leEU42pTLSFaMkkkpPderFs6jF+6fn3L85lJQlRO\nbX+5QogNQohNQognhBCPCyHe6d6/QghxuxBih/vv8uybS2ViHLagDUUxHfsmZuYzbVOvzrjtO3eZ\nP8Y0MLsNkkwB7DzhqvVLsPXPfzbQwei1r/aqZ6/zbuvtOHfpcE8dwYf3njTeHw5C+IVbi9HrVNt8\n6ZqxwN9tntVyj36lrBhbRpQudVLqDbcxnCRJ2T793cQSwEN7TvXWQFpQkh6v0hhuU5TjlS6Lwq1R\n74JZCCoAACAASURBVKkQws2K9elZob/30otbnqM/3m52m7/81rZE7VNPEcLpJ9kJ9jd+3m52n6E/\n1XHw/poITgn8rpddimUjgwgzFdInouJLEt5sAPgDKeWVAF4A4HeFEFcC+GMAd0gpLwFwh/s3UYtd\nRye928HCra2uec9tuHXLgczb1K2nx89i1dgQlgw7Fc71jsWTh89g97FJnJpyAinRdTzgPldACBGs\nTdJFJCOqD6Gvd+miwZ46EVGdnKiaH0UYdfPw3pN49l/cBkCrtJ/wPTDObsN+DlWYP9wmunBrt8Nt\nTkzOM+WcOhL++o1PzODU1Fzkct3unwWKcbwK87Mr0hpuE12TyxICAiKQvXN62r9gtXKsdbpvfTiO\nMZOkgz2FabiNlE57DZMAhpY1ryNNtltDL/xZWJbz/dOnQr7qXKeo9WVr/dm/9OwTIiqPtr0WKeUh\nKeVD7u0JANsArAfwagCfcRf7DIDXZNVIKid14JjT543TTlYt7ciqDzu5T5uGrmi2HZpAQ6topncE\nPrrpaQDOWF0gbkaY4FUJK6MsBX29Q3Urk05ES+FWt7d5YrK1M5u3rftPe1e7VOcmSWfY9D6JNo8T\nlZ36Wrcv3Nr5ul988UoGGakj4e/fTR/8AX75Y/e0LOdnXHRZk0TA+/LvPzlVmJpTeWaS1NxMEv34\neFILSJmGizQDw21aWxkuTB/3voYDXZaXSSK9/VEUEbO/SktcOx7cc9IPaAH4uWvW4f4/vQk/d7Wf\n1cvhNkTl1NEvVwixEcBzANwPYI2UUpW6PgxgTcRz3iaE2CyE2Hz06NEemkpVEJVJcu15y/JuSleG\n6hauPndp4D518J9tNIP3R4Q8ml6QpLXoV5rHef2YnsVV3Om5ZssWTrvT4+10a7f005IRP/DmX21q\n/wabTgSFe6XNXSKlFhIVRziTZHK22boMZFdXtos6gwgVV/jrMjHTwNNaVmpY95kkznCbe54+hhe/\nfxO++OO93a0oZX52QjrrE4j+DfrT6PqPN7QgyPJFAy3PCQ63aV1nzRJ41TV+oCDuAkW4SK2qYZSs\nJom7jtilehM3y85ATbR8VmuWDBd+amkiai/xmZMQYgzAVwH8vpTyjP6YdPZwxn2UlPLjUsobpJQ3\nrF69uqfGUnXI2OIdxT66LNM6DOFxvEmozoK6MjGnzXKT5rjaWsaZJFe8+7vYcWTC+3uuYeOkGmpU\ngBOiobpWYK2DTBKg9aokh9tQ1al9z5AbUH1kf2sNEVt2t3cuenFMKp6kx8JejzWW5Xw3D5ycBuBk\nBhSBHzZI78Cjv1MXnzPm3bYsZ+ivHviY1/ol65eP4KbLzwEA7DrqXABpV5NEPU9JMvOdWo0QAjPz\nNr659ZBxlp3Ac9x/s9y/yIhhP9dtWAYpzUO+2F8gKr9EQRIhxACcAMkXpJRfc+8+IoRY5z6+DsB4\nNk2ksjJ1cvToeiCrpCQHFCe24zc2rtmmg/be41P4zU/c7zzXffKV65bEPqdb+pWPwZqVyZWW/W7H\nEggOq9q0vVhZYx1lkpgKt+qP82SPKkidwwwP1DA8YGHZSOvV4+AU58mpGgNESSUu3Or+23XhVjfD\nQmVbNpr5fFFf/ZG78YHvbW+7XGp9o1BNEv0iSk04oRg9kLH3xJR32xICv3rDBgDA1JyTYaavKypr\nQr+720yyc5eOxD7uzW6TceFW035voGahYUvvfdOXWTHaWseFiMolyew2AsAnAWyTUn5Ie+gbAN7o\n3n4jgFvTbx6VmX4CrQQCDCUJjOikoXBhZO0Rw33/vvUgdh9zUobVAXVMq8fy+MEzeChiJplO6Qds\nyxKFyO7Ik765fkcq2fOMw21K+H0liiKlxPjEjH6Hd3PNkmHjSY0qYNgpgWxrBlD16F+Xxw+ebr9c\nt8Nt3GzQupsqMN/McC5ZzSP7TuHDm3ZGPp7F8VpP5tBrwqkpgPXf6LGzs95tIYDBurO8Cgi0q0nS\n+toxNUlC9VeuWOcXPf29my6JXa9a6/bDE7HL9SJquI2qNaJnAyvrlg5n1h4iykeSTJIXAXgDgJcK\nIba4/70SwPsAvEwIsQPAz7h/E3mOn40u3illdBppkU9GW0YJddhYvePjX30ILvPaj7YWp+uGnh6a\nx1uqtm2wbqFesAG5qjlJT9RaZrfRbvNUj6rgEz/ajee99w5sO+SMntX3bVEzfsSOkozBTBLqlJ4Z\n8OE7o4MJSi/DUqQE6u40rWdm5tss3btkGY3pEqHX1WuJCkMmia5mCS9I0DAESZK880mGuqqLGfrF\ntLGhetTiAIAXX7wKAPCtrYdil+uFk0nSev+g+yaqenR6u8OFa4mofOL3PgCklHcheh94U7rNoSoZ\nMhQLLeMQG50Mjcn3x8OaZoKI7xVcdM4ogO7S15Owcsja0TsFamstAbSWfMyf3sn2apIkuEho+tSW\njgxg1nC1iKisfrjDGRI3PjGLZYumMdewvf2ZJYTxdyAj0s7bsSxmklBn9K/L0YnZ6OV6DCeo77oK\n7N+98zhm5puZTtuapD7H5GwDQLrH7sjhNm5NEr1ZjVCmSM2bGtwQJIlqpHZ33DaHP0M9vrBuWXxG\nxgWrRtuuv1fOVMSt26iGaKlMEn2Jol0oIqLOtQ2SEHXLdMjyK5EHI/NJ63z0W3h2h047MHrHb2zI\nGfOfR5Ak/NppMQWCBASkLFZAwZ9JKGEmSei9O3fZiDdMiud6VCVTsw3c+Nd3AvCvfoZT75Xuz0NE\nD8+lhUhG3I5asOvZbYRzHNO/7lkFSR47cBpPHz2LV1y9tu2yKsNrdDCdbroQwYsE+nBoSzj9rlPa\ntL/6sCNLCC+o4g230d6wqOOqnt0TOwVwaLiN/rxVY+1re2xYMZJ5kMQ0BbC6a4c7m5++CDNJiMqP\nk3dTZqJOoJ3HSjrcJmJ2B9Pxv93JtEp3zWp7g8NtRKAjc+/Tx/GB723vObVYP5HyphAVxRiSEqxJ\n0npfkucpasw2UdVMzvl5X4FMktAP4Yv378WWfa0z3iThnC8UYa9AZRE8tsRlITi6L9yKwAwlQHZZ\nCb/zhYfwzi9twemp9sdddRFl+ehgKq8dngL4+KQfEFE1t05q7dIL2I4N1b1MCtt9b/Th1FGBDP2Y\nGZtJEgp0dRpfqFsW5jMMkjRtc7aMmiHo9LTzvul9WgZJiMqPmSSUGWO6tn6vMN4sNGfqYv9vL+jT\nxbpUdkNWmSQDloU1S4bw6uvWY9+JqcDJ/+tvvs95bUvgXS+7tOvXCNS484Ikxag/oDfByyRJEiQx\nfJp6hyfLKvpEeVG/Bf3EyZ+Cs3Vo2p9+/VEA3c3+YQlmklBn9H11J/UsOiWEaNmnt5t2tltqxpj/\nSDD7my0llgyn20WP2izndYLv37wtMTZUx1fecSPWLh3GvpNO29V7s+e4k1l56+++CJeuWYx2En2G\n8DPZOlG3BJpJxtJ2SUoZqOFy7tJhHDw9g3MWO8GhqbnWoVEMkhCVH4MklJm47IpQrKFU9KsFcQfz\ndifT6iCa1bHUsgTu/eObYFkCv/OFB42tOXiqdQaids5bPuKl6uonWN7tAn6wKqvGlhKnpuYwVK9h\nZDA6ndo4u417uwgBIKJeqf2TqbaAZThxVLo5gYwavkMUSRpvti7W49fKEm4miX4sy+h8e/2yERw4\nNY3p+fZVu6SUXQd+TOJ+g6bZ25q2jZHBGq5YtwSA319RtUrUqq48d0n0a2q3Y2e3MbSnEzVLZDp1\nc3gK4C+/40acnW14Q7Km50w1SZioT1R2/BVTZkwpssGrlhHDbYp4lu2SEVNgmgu3GpbTbqeVSRL3\nfunFxna642Z1vZ646CdYfuFWlbXR35Mi/fVVmw6emsaL378Jb/jk/TFPNN/N4TZURQ0tHcyrCRCT\n+dHNUISiZJdReehBuvjhNs5j3e+fne96YLhNxl9WNRtKHIn0L6DEbVX4pRrNYN04VZPDtiWePnoW\nH7z9KQD+NLjtxE8BHPwMO93sek0ECs2m7a4dxwLtP2/5Ily+dokXJPnU3bsBBPu0jJEQlR9/xpQZ\n83Ab918ZLtya7ms/vPckbn/iSLorRWsGjNDub1m2zTHb8ookZn/2fcIdf2yHOhLd9AX15+gnTKoT\noT7XIp0ULVvkjOs+NT2Ps7MNbN5zMnb5+AwhovJTv8857QqsfpISdWLazckIM0moU/rXbOv+05HL\n9ZrAaCrcGj5Opm1mvn2qSjh7oVftfoPhl5pr2i0z4ADOMf9Dtz2V6DX1GV46Ca52ut11y8o0SLJi\nbNDY/qUjA7FtIqJy46+YMtN2uE2GsYHXfuwevPWzm1Nfr5TBdgdud9hNq3mZJGm0LN6LLloFoPUK\nWa/ZHoEUZS9I0n2dFmXboTP4//79iUCF/V6cu9SZRjBZTZIoTCWh6glmkrj7JCv6t9Lo4jfpzHjV\nVfNoger02NT17Db+K3q3sircqto4k2C4jS3T7yPFvaXh/kvTDg73Ucd1W0qcmp5DEq+9/rxEr906\n3CbR6j3Z1yQBrtuwrOX+gZqF85aPeH/PBWYEyqw5RJQTBkkoM6Yx7VEdn0B2RgoHl6w65BLSGAxx\nquOHAhBt2qUuNGRVuFVnaVeBdN32BTeuXOSszzC7jT+TTPcfwnu+8Tg+dfdu7Do62fU6dF5l/gRt\nktL8GeuPE1WF6QqsU2jV/D1/9nmtJwvtWIK/G+rMmZlGouV6/VYJ0dpfyCrrSa02SSaJc0EmxUwS\nRP+mgdZ+V6MpA8VH/UyS5H2WjatG8aHXXeusz5ZegdMWob5Dp32imiVwNuH3pRvOLtLcJj1bZlrb\nPvXZLYqpfUZExcYgCWXGFNj3h9vk2pTUtGaSqKyJ5AEhxcskyeFXqDo43XQGv/3ooZb7/uE/PwdA\ncHYbtS6RQibJ+MQsAPSUSRIISCUI3Mw3bXzge9ux+/iUMVDHmiRUJeqnoP/GmtpvOCqAmrAEQYBl\ncXYb8m3ZdwpH3X18lH3uTDDt+Pv07nbQKiAYnE0nmy/rAbdQeqKaJKEhyWkwbdfiIWf+hpYgiW0b\ngyRPHIoe+mSinvdHtzyCZ7/nNmOWjl9XprvZbeabNh6JGZLVq6hadEBwFpuVo8GpkD/wq9fi8295\nfmbtIqJsMUhCmTF1M0wH6f/3m9fnUpcjDXHDhDoebpNjTRJ1HG8dbtP+uR/7j6dDz5GB1FtF9X3S\nqEmiOr69jDPWA1de0bmY1W0/PIEPb9qJR/ad6vo1icpC/T70WSHUCYxA9IlirYv9Vdz6aGGZb9p4\nzUfuxn/9/IOxy802nODd+mUjsct5IZJuh9sIZx2Bwq0ZjNzQgwNJpwBOs4i9aVrvf37zc/Hld9zo\nPB56rSNnZgPv6YYVI267/EyPeoIojurfPPDMSTRsiUbMsBgRek5S5ywexlA929OZqE1V/bixoTpe\nevk5gcd+5SfOw/XPWp5pu4goO5wCmDJjnN1GHR+1hy5fG5xCrsjhEhmRdpl0uI1ODQHJZbiNIahh\n+tv4XEPvQDX5gDaFsO2dYEVn13QqrZokImL7dfpDpk+kyN9Lom4FMknsYPFlE9P+oB0hBAseEwA/\nKNeueLaq2zE8EDz5nWvYGDScEHdduBUCR07P4N6nj3v3ZVGTRD/26MfNKFJmMLtN6Pj3U5dpJ/WG\n19IDokP1GkYGam6tEvcpCdo3MhAcbhJXq07pdLvXLx9JFLDpVlzAquamAl+zfmlX+0YiKi5mklBm\n4gt1ybYnpcUkQ8NtYhc13OXf6U8BnFLTYnhBklDn7+6dx9o+d7AWHSQ5OdlawC2VTBL337SG29S8\nmiRxr+k/GHclixfEqQq2HZoAAMw3W7/QcTVJLlw12vFrsSYJKUmn11VBkpFQTYcjZ2aCC/ZclASY\nmG3gc/ft8e6ank+/vkXU7ylq6I2dck0Stc4o6pUuX7vYu68W6pzULeFODexmwSbouV20uv3+IpwN\n1GkGjUDvX4M4UkYPi9526AwA4PGD2Q33IaL+YJCEMmPKJDB1FEoy0gaAW5NE+9vLmmgTEDHxZ7fJ\n/g3Qp+/TrRobMi0eMBAqQiDhb/fh036H1ZvdJqL+SVITM/PecxuGE7huqL5e3NSO7S4extWfISob\nFYDU09/f9MKNAMyp+S+5xJkh69ee+6yOX8uZfrS7dlK1JB129ch+Z9hjOBMhLFzPolOm4+8vf+xe\n3LrlQFfrixK12VGjT+LqYHRDxAQ+AX9/oA9vUkOelFrNmUXGa1aC9nXSv/Fm1+pwu03Fd9OUZOhT\n0kLDRFQeDJJQZmKnAI67olHgqEm4JklPUwB7NUlSaFgbXpAg/L4neG0VJFk87I/OU1dVdh3zZ5/x\na5J0H0zYd2IK17znNux1i/bFjV9uJziTUPvhNvpjHG5DVSalxNSccwVbnRz985ufi/f84lUA1PCY\n4G/FEgLXblhmHOrQjiUEM0kIQHygWqeSCMOB/PDXyJtVrcv2RD3vrh3tsyw7ERkkiXjA1mp/pdYG\n7fbv/NRFgcceP+hkROizV4UzOeuWQEObGjhJMCOcjWLa3JbhTR0HSVr3V2mKq0VHRNXFIAllxnTI\neuHFKxMvW0RR08NK93/BZU3P92+rk408pwAOd8iSvPL57nS///vnr9Se1/pMf3Yb5+9uzomOng3O\neHBqar7zlbj0l1ftjR1uk7C9PNejsvvKg/u92/e4tRj0/ZBlyPxwrqZ2J262HFpYkn4PpJRYs2QI\ndTdIv2J00Lk/orfQS+FWk/Awn15Ftds0/Oj1H78P/7blYKpDcQX8IW9/+yvPxh+94vLA4yog8twL\nluNlV64BAPyFGzRVapZA0/Zn3UlyYShcp8P0Pvx49wkA8Iqvdtoncrato6d0JO3pmImoHFi4lTIT\nPiH/m195NqZmnZREieBBrSxXGcNXFNQVkPEzrdMZmrbIdF8eNUn82V1k4L1OcuCvWQKLh+u4boNz\nhSk8DbKi1utnkvTuycMTKazF/y7GF26NL5LDPhJVhT5MbtA9CdWv+AoISNmaxdX1iaj7rzOEgD+k\nhSxpUVTnZNw/DfeOKxGZJN06GzFMIu0gSdRmG35muHdXa+AyzTaYfoPqfawJgff84lV42ZVrWmZr\nqVsWGrZWkyTRcBvz6+iWLxpw/nUDYR1vtci6Jkn3AWIiKi9mklB2DBmUXl2HwNCG8sx8EK5JstpN\nBX7LZzcHquOrZZPoeZq/DsYFN+1gwdwkARo71FmNep7fAXP+TSPwNdxmPHoc0+vHtcmOj5Fo6+i6\nSUSFoH6/a5cMY8f4WQDBEx7LMp+MdnvSFnWCSwtP0uOCmmpWfVdVaaxwoNsr+tnlcfSnQ4EAZcnw\nQFfrixK13bE1WlKtSaJlexoeV62wLIH1y0bwuhs2tARTvEwSK3nzwlOGR108UoES1YZOiIyjJBL5\nXMwiomJhkIQyYzpmlf0iYvhK6OolTpBk5/jZrgt35VKTRCumahqGEqcpJWqWCLUzZriN+3cqfZaU\nzqpU2+MuYrYrKNhzMIuoIBruD2F0yA9CrlvqF2w0zW7Ty3AbdYLx2o/d0+UaqCqSDrexpXMy7te/\nMGcoquBDt8dRvdYWAHzhLc8HAIzmlEkSN9tP6pkkaopvQ88/nAlqMjPfxNcfPoDbHj+SuH0tw20M\n22uH+lVdFW7NMEoSbp/uf4aGLRFRdTBIQpkJHwz1g0xrRyeHBqWgk7qnxoO2YUMv06bcy4rqdDiZ\nJPpwm/bPVVf09NldzMNt1Gt1f9U4zWFX+pr0TJoo+kmhKhz72uvX42euWBO5XqIysm3nN7xo0DlB\nfMGFK3CBNrWvqYZIL5kko0PO62zZd6q7BlNlJJkC+OYf7sLXHz4A2/aPUVllIy0dCWaMqGE2qe/n\nOyzcCqSbvSDgH/+MddW843f0OsYnnGHFDS9ttP3rJsokkeFVFbEmifmxX7h2XXYvTER9xZoklBnT\n+ah+nJERt4uSbWIcPx86WMaNr88t8JPgdbwpgEONWpTgapntFmoLDreJziTxHuti+1tOzDpfReST\nnWkC42qS+LcvWj0GAPjQ664LPN9ZjmESKreGLVETAlNzTvbbUD24HxBonVnKbj2TSeyKdUu6eyJV\nTpLZbd777W0AgOn5pj8trHdJL/j86flmT+1R+3olq2BMVKZD3ARuaWcvToZmtNJ5w21i+jQbVy7C\nM8enOnrN8PqMBe2BFDJJsuPs+syNCs/eQ0TVwUwSyky4UxAIkOj1H9qcvPbDnuOTuPrPv4dvbT0U\nuF8ieLBM4/CYxyHW7/jJyOBUFNsbbhO/3aqz58dIOv9M0y7Kp7PazLChv9aX3vaC9F6YqGCaUsKy\nBJ5/oTPbWLijP1Cz8NiBMzitzS7l7Pu6owdjD52e7nItVAXthjWGeTVJIoIXKjup2xoi4ZiA1X2M\nP1bUsSfu/UjzgpF+/L7mvKWR7Yg76f/4b90QXGeC120Z2mNMsJXGi0/nLB5qXdj0GjFTjEsp8dSR\nicRTT0etI+qzYJCEqLoYJKHMhI9ZQsA76sedQBeh9sOuo5OYnGvi3bc+hr/85hNemmrrwTx6HUkP\nyXnM9qCCJLuOToZmFWr/3KbtPL/udgYuXDUWm0kiergS11qUr4eOjfZcZ6hAfIdUf2zZosGY9RKV\nW7MpUbf0opjB3/Oz3ZOoB5454d/Zw3AbfaaQYxNzkcv94x078BufuK+r16By0M9VT05GfxeA4PHW\nq6sVWub7246gZgk8y52qvlPh77R+QSFNUeuLGwKaZk0SfU3hITCAf7yOe8lL1ywO1HBRw/XihPct\npmN6OElNPWWwnuwURSA6CPW9x4/gZ//uh7hFm/a8U7aMzm4xvZdEVA0MklBmTH2CJIeTQhxz3DYc\nn5zDJ+7ajYOnnKufHV1NNc2uYnqpHLb3fLcDeXJqLhQ8aN8RVAX0zls+gnf//JX469deY65J4v7b\ny5W4liBJSv1UVXitp8KtRfheEqWgKZ3hNuokLNzRv+kKZ8aPhvaDsWOuprazYbl/AhsX+Pzg7U/h\n7p3HvWFAVD16UOAbjxxsu3z4OxreTw/Xa9iwfKTleUmFAxFZ7ecjpwCOOexk1RbzFMDtC7eGH/+L\nV1/V9rWSBHrCNT/UhTI1PXlbMa+xz60vtv3IRLJ1mdoHGXnxrm6qgktElcBfN2WmtXCr/mDw8YKN\ntmk5HKr2RR3MTRJnknTUsu5WoIIkzxyfCmaSJFi97Z5QCSHwX158ATZqBR51O92pRHu5Etcy3Kbj\nNUSvK5xJcna2Ebt89Ip7aBRRAdi2RK2mBUlCl0lrVutvWKK3TJJPvvEGd53tl79v1/H2C1Ep6d8p\nU22MsHaFWyWAq85tHT6SVOtwm5xrkoRnkdKiKalmkmirMmVFhAuvR1H7hrol8PKr1rZ93WQ1SWRg\nOXWzk0wSZ92tK1freurIBF70vju72rdIaZ4RCIi+n4jKjz9vyowEsG7pcOC+qONvltO3dSN8pUW1\nz5nZpfVg3uOLpbCSeGPu7BJb9wdnl0gyPvyxA6db3o/wtH6A3+HtoW5rpsEy2wbu1zpIM6GCf+q9\nuOUdNxqfn8ewKKI8qMKt4aEMijcblPaD7CWTBEi2X1D7qflmsY4HlB79O1XvoJ6DPo29Ts3U1K3w\nc7PazUcd28LF1PW/syp3ETdctl3yhmpT0vepdbhNKzs03EbNOPSzV64xLN3KL6oevcyPd5/AgVPT\nuHXLgUTrDLcv6mrU6GAdL7lkFf7mV57d8XqJqNgYJKHMSBkci65nXcR1gUcTzLiStXDnJJBJot0f\n10/4++/vaLmv2yFIcYbcqy0//+zoqeiEEHjWikWoW1bHNUmkBMbPzATXF7Gcei0AuHvnsURXCnVp\nDrcJP3WuaWOJNt1jyxU898/wTB+t6+UJHJWbKsasTpbCJ6vqfrvDfUWcJLWm9KnKqZr02VzaFb3U\nvwX+MM7WoEIvxTNbhtugfd20bkT9fsLZD4HvfqoRG39dpiCJetV2FwPU40lrx7X2pSJqkmivu2HF\nItz7Jy/F7//MpYlew//MoturviONNgHY09Pz+MUP34VN28f1FkYGrCxL4HO//Xy87oYNidpKROXB\nIAllRg3T0HkHs3DKbIdDQLIW7gD8/+ydd5wcSXn3fzVh80qrsMo6nXTSZdBxkTuOA0w2Bow5bIMJ\nNsn4NcG8DtgEY4N5sbGxjRM5GdtkTM53hAscl3NSOOkkneJK2tXmmel6/+iu7urq6u7qtNMz+3w/\nH320M9NdXd3T0/XUU8/ze7j8f4xt8Ixz7NWP4zGidO6xNO2pUQ5RDDurr3ErGWuW9GG+afmMP5O5\nSKXC8JSzRn3v6frslQC2X7/lC3fi23fH55zr2hBkEm71TfA4LjxtxH/fBe5B+40wG5HiSIhuYe/Y\nNBjzfqtB8Ur7/7zSbWRM0vCa5CTpWuYlx7kuIlFF3C61sEgSjZ2RBHVP795P3aSWsLFMXUeQnSRx\nwrZp0WqKmabbiM8NL3kwKldzbASjgdYu7Te6P+xjOO3o0m2c/0W/1cgdlX3Hp3H3/nH8848edt+z\neM7+KoIgOgJykhCFweFfKWIsIt0mxxVLf7vpGlP76bbDFQeKst3S/jre/xuPS3YsjbVxUiq9GQcH\nMDJQj1Wa761XMNdsBZwHse3zoGiZTqxMtCUbrIfG52Lb97UR+0Y6xEqVpUz6ZCxDI7Fs+jkEkZTD\nE7M4MdWQNEn8n7vpNtKELaoMphEG6Tbis5aVLAKN6Bzuf2zC/TuJ0y083SZbKmRQuDU8KiELpiWA\n5Un8ldtW5nZ8nyaJxvmgLnKEUUnmIwmg1STJ6IRwNUl0nykphXGRJKJ/TfXZR8skBLHoICcJURhq\nCKXvM2VdxVdxJUfzJO2ENuAkcf9XSgArA+fjNyxFvZpsMI2KyjBuw2CbnmoFc03Lf91ND6McYHS4\nF+970fm+94RNkcXYUZ02We4E9T5i8F/XYGqPYySGPBWzaK0QRJnorVVx8enLAqHoAvFaTbfJatw2\ndAAAIABJREFUEkniTmQMfkBfu/0AHjg4Eb8h0XHIt5pJmsz4jL1gMOH8rz7X7dSxLP0Ji6JK36YO\nMb5sUYTPRfUVgRBAB4orL6stAez8H1vdJqNQir4EcDYnRJQmiSpOHZfK13KdRf708KL0YQiCKC/k\nJCEKJJjHKQaxj/18t/seYwVGkqTcL5Bu43QqoEmScOA0dX4kyck3vV699Qrue8w/8Xjo8Cm87zv3\nR7cf8v7vXLbJ91qcWxZhW3UBOW0kkAp3+hKlsRAXSUIrSUS3YHGOwd6a+3xWJ6viJ3DT7jF89sY9\nmJlv4Z4D45iZN08DVEmy2n/djmN47oeuS30sorw0pIewiRPg0s3LAQDTzr2nPrdbFs+WBqbs6kWS\nFKNJUlc8OhOz/ipr8m8si9aKityStlkx/sUcU1zr1JdcF0mSpT1Ef2dqdlAzJkpNRLHJl8EWB6bx\nnyAWG+QkIQrD4mq6DcN80zYAPn3DntD98jRN8ku3cf7XfCZTYSzSsLlxV7D8nNZeSdhtkwF8rmEP\n/o2m30j4+HWPRO/IzSJVPCeDwcahbRQTRcSdNCkeEUliGm5M6TZEp8O5PUEVE89pxfkhJkJfuW0/\n3v3N+/B1pyLEL3IpzRvxAwqkUtCPrdto+jRJorflHBhwhNxFxaNgmiTPFN2g7lpcJIn9f71mH0BU\nclLvcVnsPM8SwDI6e0E4GMzTbcz7dt66JdJxgmSNUpPbURGtivH9wUOnItsQl58pkSTkIyGIxQc5\nSYjCOD41Hxj4wmzeVCkgBuTVlJtuo4SF6kTfhvvqWDnUq21ndDj4ftZ0G9MVrws3LQMQL1wWbN/M\nCeMKn0ZcH5Nj+dtM2EBIW9zx9ERFkngrTCGRJGQkEV3AXLOFhw6fQqUCTM7Zq9hnrxn2baM6epNo\nJIWRJN1GMNtMH7lClJM4TQiZRstyIy/E81ld+LB4trSUYLpNMQ96Mab3KJEk6ngsX58saUQqPk0S\nzSmKcTvuWgqHVJLL9PFXXowXPWE9AP3v3+I8U5xmZF8UfaW4aDixndymWGQhCGJxQU4SIlc45/js\njXtw297jAICpOS+UVNWEUGax0p/t1yQJq76jriiozgNhYL34ovXoqQV/XrphVjf4FqFJ4pb1TLE6\na9K+q46f4amSpyaJv93g/ade4lv3nADgrVyGtkWqJESHMjXXxN98+wEAwI7Dk+7vYdlAj287ddKx\n74Stm7BuaV/qY8dp+lgWx6k5f+rB1Bw5SbqNhpTuEDfMXbp5ueskaTnOA3X4stNt0vcnKNwq+pZz\nuo3zvzgfL/1DcZJI16eaZTBVkO0MnSPoT599FpYN1LGkvx7Zjptuk+DY60b63bQpHTxpgwphVRPl\nZkVaU1wKk5s2LPePZ7vHCILoTKLLYRBEQvafmMG7v3kftoza4mSXbF6OHZIQmU5rgzHmn3jmGkmS\nl6aFmSaJl//KEp9HRYp0SBRJYripGOQTR5IYbu+lq6S3JtTbI5Odquwc0CRRviAR/rxupF/bnDir\nx07OZOgUQbSPX//3G9zn8eRc0/2JBIRbld/w8Um7FOmHX35R6mPHrcROzjcD7z1wcAKjw6OarYlO\nRY6UiHu+91QrrlPBc64E0ySzpNsEx/BiZsNiHBWLJ+Isguk2xUSSyOjG6NddtQWvu2qLwb72/2mv\nk9Ymy5hu4zlg4w2GONtK2Khyf6gEMEEsTiiShMgVoUS/++gUAL+xzZjZBD1fTZKU+ym98LUjn5Oy\nnzAcGEvgoHEaUQdlUyzOjZwqurKeJpjm43rVbfzfeRICFWdyc3IFNUmC6TbcdZToGO6zV9iOT83n\n0ieCWGhkh7UcWRWXcrDrqL3fUF/2dZWwR5UuDePUbNBxQnQ2siZJ3Lg12FvDeeuWYHS4F799yWkA\nNILbGYVb1V2L0iQR46Mq3KpGksiaJHlWt/FFwOZQDShpz6LS7TKn20S0HdSwiW5L2Ee37j3hCfaD\nhFsJYjFCThIiV4Qx3V+3UxZ8wq1goakefpHN8qUzWJxLmhvheKJmIaGfMaKv8vFMuW7HMd/qUxii\neZ24+1xE7r8aPROGLkw1aR5vkXo0ahUl9Rq3LB4ZitvfU8XS/jpu2XMC33CELAmiUzihOPcYY9r8\neyDoJBHOlVxWe0N+5PLk2X0vphIF0XncuveE+3fc4/41V27GxuUDuOUdz8DTz1ml3afFo5/bcQTS\nbUTqRuoWw7BbrFft9oUekGoTyc7CrOV2w8jyO3b3TdhEVLodzxipIbf94Z/uwqs+dbPUtrrgZRZJ\nAgB7x6YxMdvAbMNKpKVDEER3QE4SIlcOjc8C8ARK1cFYtoPlKAGfPEmeE+Wc2uIcODo5B8BvuAdC\ndSFHkgSJchrIhl6SucGq4V4MG6zwupEkmosSt2KbRLhVtusyR5Jk+P64clNVpEkhYH8/n7/5UVzx\n/mswNddE07JQizFK61WGnUcm8ZYv3ImfPHgkfecIYoG5RnO/hqXbhEkhZJmzuau9IZ83NA70pFFv\nRPnplbW6Qr7eaoXhjU/bivPXL3XfE+OXrnR7Jued8rroSJIViqi7Oh7fuf+k+3fceJTs+FIaT4br\n1S80uxJeH083JLgjR8ZoIKntv/v+g/jZw0fdz1QnVNz3Kn8fs82Wm2q4YqgnbBeCILoUcpIQhSAG\nFDmyNCzdxo668N6/fuexorsXj2YgPXrKdpKsXSprVugnF2pqhwmyoyNZdRtg66qh2O1cTRKNByZq\nMmKa8iKaqGVIpM7LML1z30l84ZZ9XrsQmiRyug3Hv1yzA4+Nz+Lg+GxsJAngdxa9/X/vyaezBLEA\n7Ds+HXjPNN1GkKnCQ8yu+kgScpJ0Gxxwq7+FjS26sVPcPuozfL5p5SzcKiJJ8r33RLdPXzHge18d\ne2UHRp6RJIcn5ty/s0RtXHHGCgAIiCzHEuF8yvozj4pSUdsem5rH3rGp0LZkp4pleffb+hCtMoIg\nuhdykhC5IoYXV/xKGeTD0m2mpbJseXrsc9O04N45rZUqPISJvoVGkkQYJ0/auhLPe/xaAMmcJKYr\nacIBoJmLRE5GkqbbnLV6OGbLcG7ec1w5drrv71WfuhkPHJyQ2vH/L/7uc9LCTs020Gjx2JU7+WPS\nJiE6iYbyw+eSlpF624c6SXKYs+l+0g8cnMAJTZlhiiTpTsT9Fvb1anWwNJPsPWO242+mkb4K0kJp\nksw6feyt+aunqfd4XhEfKk/ausL9O0vUxoWblqXaL+qIdrpN9nMN0ztR+bvvPxjaxkEnGlrsK/Ym\nSRKCWHyQk4TIFTEeifzNmk+TJFy4dY/k2c8z9zO3dBtw15EQFW0gi5olPXa1wnD1hRsAJFtZMS1P\nJ4wQndGgW8X12keohSMbXmGh+0kYVoRT0359QkDYa8cWXvOtQgJY4kTv3LDzGFoWj42CkY3WC09L\nZywSRDsIOEngOUzVCYqufDmQbWXb03rw/6qn55t47oeuwxv/5/bAPhRJ0n1wHp46I28T9JEE7x8x\nbmV5Fqv3vhdJki8PHToFAOirRwu3yi+zjKUq/hLA6dtJ67hhynd+5NSstJiRUbg1IpREd4/9+IHw\nVNmD4171OlmLLotjiSCIzoScJESuCANGrI6o1W3kSBJ1VR8Alg/25GoYp21J3U+OJKlJCfshi12p\nlx1ccdVEkSRm+bxR1W3irnlYmP1nfu9SfPONTwLgRX34HGMJr0OemiQqTGnf4hznrlvq/G1fg7hI\nEvl8Nilh0wRRZlRxZ869FD8hJimoVhj+4rlnB9rINpERB/a/P+NEEe4/ESyt3Ypw3hKdCYcUrRE1\nQgecF1IDyp95TmDdlnIOJRHn+gTJoVNhweha+fUlpy/P7fjiEp0xOpgpJTat48b7+uzzu3HnGH72\n8FF84rpHbMdZpoo7/rZldLbUfNPsuWJxuWpf6u4RBNGhZK/nRxASbiSJo3uhrjzqVigZ8ybufbVK\nZifJl26VtChyMnQ4vAiXaoQTQK5uI46fxFEgjL2wtCQdlmXmjKgoDph3Pu8ctCyO93/vwdRh7fVq\nBQOOkJtoolpNb00UNScS6vmqY044RabnW2hZVqwBKBtyJSzCRBChzDXVSBKONz99G4Z6a7hs84rA\n9rrfQp4CmYKosvBUUKI7UaMKtNsoryuaCI+wdLGshKXLZkH8/uQy8xYHbto95tvO4hwDPVV8+ncv\nwfaNIzn3AnjB9vWZ9k/tJAlJY2pallMCOPuzxfKN7yJ6VL/P1FwTg73BKZDsQLEjSey/KZKEIBYf\nFElCFIKlHVgYXnrpaQCA05Yr4mXOSNRbr0amfpjw04e8UMo/+sKdmdoSWJx7kSSSEyAQSSJpkgBB\ng0C8vnxLcFLCuWeAJPFZWIbpNmokSV+9itNXDgIIhuL7+8VjVlH8aTy+6KH4bvkIRJLkaKrqIklE\n+zPzTVxrUK1Gvp/zFvYjiCIJapIAm1cO4r2/fr52sqCbFOQxGVV/NVEOWp3INNHZcM5dZ7O20kmI\n50QXZWlZ/s/ygLFsEVNhzDUcJ4kk0F6vMtSVqA6LA8sGenCZxkbIQl7nlNVJokOrQZOobeF0k8d3\n8b/+flL1zwTzLfn+CtdtIgii+yEnCZErYpASopbqgLpupB9POXMUywbqyn72/721SmaxPjmqQlf2\n0gSdc0NEx5gYCV7+dJDh3ho+/qqLpW2l/VKk28g53pF9cjb5y2/cB8CenIhIiujqNtEGlpoOnCWP\nWjWQ89OUQWBViXOv/R8/cATLBnpCtRgEtJpEdCq3hkwKwtD+jHOZyPjfj9KgIk2S7iRqfBT3R0AU\nXfnc3p872+av3ZF3pOBc004r66tV8dZnnIlP/94lWD/Sj1/sHsM9+8fd7WQnUhFkde5nHQPDvvMs\n36FOkkTYEreEPPd+79O3YGI2KBbtjySRbTEa+wlisUFOEiJXxHgihDP9qSlw35uca2oHy956NbNh\nXMxEVook0ZyTinj/bV+9O/DZupF+X8itjJtuk1STxOCXLNq+54BtkM00Wm5ucqwmScQldUNdE1yf\nMNTQ+7zsVCEE6C8f6bW/YqgHjZYVG94snw+l2xCdhOq8jPtt6kRaM6XbhOgGRD3rfrk7mWOH6Ayi\nKsh4U1L9/eqfCIv2so35P/6/T5EOZE/Y844U/OlDRwHY0SNvecY2PO2sVThjdAgAcPujJ9ztWoYa\nY4nJqc30miTBaA/7NZx0m/ToHWg2Ih1Yx5SmjPF8KyzdJkMHCYLoSMhJQuSKalbolNBnGy3sOupV\ns5GNod5aJXO6TRFj2Rv+63bcttc2ZHyOH9WQU/7/ym37fZ/HGV7CONp5ZNK4b5ah7onqSGk0LXfg\nv+/AeHAHhzhngOrYka9PUkeC6qvJszpRQJMEnnI953Y4dG+CSBLykRCdhBot9pannxm5vT7dJn9N\nkigHbdzvkeg8bJHO8MUA8UwO3mq6lAoufZKerauGvKOwdNXp4hgZ6EGF+SMm/uoF5wHwtNrGZxqw\nDCND20X66jb2/zzmdZbGZftKfH/zTY5z1y5x33/l5Zvcv0UKlMx1O466fz96fJo0SQhiEUMWCJEr\nqmFR8TkUbNYu7Q/dv69exYnpYAhkEvIYy1RnxtFTc/iPn+4CoFS3CYiSBN+fbbTc9KO4/q1fZl8b\nU/V1wDzdRt2mYXFsGR0K2VpqH9Giaqr+SlW6PkntzKBgbY75NmDBSBIpb3muZRmk2+TTHYJYaBot\njpVDPe7rl112WuT2umdKHre/OkaEpfptXTWEmUYrhyMSZUO38h+2jfvaeWPHYW8BwZ3A5mzJFiHc\nCnCcI03WAc85YnGOO/edxPa//iG+dddjhY4zWZ0/WcsSa6OHMjqG3D2ltsVY32hZqEvj+jbJIaaK\nWQN+Yd0/+8rdniOOxn6CWHSQk4TIxM8fPoqfP+x53lXnglzoRKygrFnaGzrQzjdbGJ9pYDaDcVy0\nx1+eaKgIZ4K8WvSG/7oNF773R7HtcnCM9NtaLUl0WUyFW9Vok0bLi5yIO1p0uo1YFbRf13yRJMks\nsiRpRklhTCPc6jpJbMdUby08NBdQIkkolIToIJqWhf6I0HMV3TMln3QbP2HPuuWDPZieJydJt8Hh\npZNo9SlC9tvkiL3LkUfeBDZPTRJ7TMv7+W7x4DgqV7PbOzYVeD9P8moxvXCrvd837zwQ+Oz6nccy\nadGFPVsA287pkQxReSFEtxilLtSIVxRJQhCLD3KSEJl45aduxis/dXPo57oBNSoq4ew19kqLzsNv\nSpFDWW+tghVDvbHbTc97ua4iFxmIn1iL6xVVFlPFNDxX/SoaTctoRS+uK6rYbJZ0GzXTKk/h1gpT\nSgTCc+o9dGgCAGJTvai6DdGpNFscA3W9FpIOca/LItssk8Wg1yRQJ0cbl9vRdEv6am6KI9E9yFED\n+uo29v/qkLbEXUDwC2sC+Yz5zzlvDQBnEs3yf75zjdZINUQ4vcgJedazqqZ8Bogz+pdrdwY+Gxmo\noydtw9CL7XrpNpavgpD89wPOuC/TUL4LiiQhiMWLucVEEAaYpNvY23HftqctH8Cjx6cxOuw4IDKM\n5HmsKoVNzvvq/pXYsEOlkVVhYJ7RFFHxQcWKLdFroxpe9spWuLEq4DAzELjGSZI0MqSw6jacO6uD\n3PeeVybQ/v9JW1dGtlNk1QGCyAPOOeaaVuBZ1WhZ6EsSSVIJRsXlIBsQQNUk+a/XXIaD47P4sJPe\nSHQfaoqmTFjFGhGh2PCNjfbfeTgV/vm3L8DRU3PorVXt+7yQSBLFScLEoojyOytgQp5Xm2mvtXw5\nv3P3Qe99xxY8d92S4E6GaMtDO3/Ptyyl7LI3iOuEW9WFEk8jh7wkBLHYiDX5GWOfYowdYYzdK733\nV4yxA4yxO51/v1psN4lOwUS4NVDajwEffcVF+LsXPw79jmGfZRWnyLFM1awIV+BP13/PaDLf31yT\nxP6/7oSevvTSjUaTHu7oeYQRVQI4sSZJoLpNfpYqY8CxSU8bRtYkESzpqyMK33WmQBKihHzomh04\n+13fdyuMCZoWR3/d3MsnfsanpDKZeUxG1Z/N5Kx/orJpxSCeuGVFbKUpojPxRZJoHqJhQx9j9iJC\ny5duY/+fx33ZV69io5PSM9e08NGf79ZoZKVHV8FFON3V42TV/Ygk48qD6nw1RT7HOx494S3QwI6k\nyXLOc0569sOHT7nviaPd7ZRXftLWFQD8/W9oVrNUp+2PHzgCgPTICGIxYmIxfQbAczTv/xPn/ALn\n33fz7RbRsSgDsC+SJGJ+ec7aJfitS06LXGEyJRdxwZD31ZBQ1TZztVRCGog7rUqFgbHkmiQm5ywM\nyUaLY+uqIWxbPWzcr0hNEqW6jbxSkzSSRA2gyS+SJHgOcrqNYGQg2kkiryaRj4QoI//5i70AgPd9\n537f+02LY6DHPHhUTCbklfu8xRUB/8RGt31SXSOi3HB4JesjhVs1t1q1wtCQ022sYlMhjk3NZW5j\nfKaB//zFHszMtwITbeEYUMfwItJtxAJUb0onh2DdSLjwfhSy86GuLDY1LcunZZaUx21YCkAtD+29\nGuyt4d9fdiG+8+YrcZZk9+g0SZqKESIi2kiThCAWH7FOEs75zwEcX4C+EF2AavPohpWoocY1jDP0\nocjBLK76ybZV9gAc1f+wsE0xYa8ylkK4Nf6cz1rjGQdiazOnVHRfRFuiy/Uqw0dfcZFBu0GKEm7t\nqVUCUT+WxX2ntrS/7q4khkGrSUTZEWLMX7rVKz8+PtPAfNNynYAvvnBDbDtbRgcD72V5tLKQ6IF6\niKhiHg5zopxECbdGUaswXyqq+KuoId9KL43m8pkb9uAvv3Efbt17AvtOzPg+E9ehpaTMFjHOXH3R\nBrz6SZvxmxdvzNzWO593Dt7y9G2J9pHTWHqqFZ8To2Vx34JaUlz7R7qhLO45SratGsLIQA/OW7cU\ng72ek0jnJAmzvWjoJ4jFRxZNkjcxxl4J4FYAf8w51yqsMcZeD+D1AHDaadElB4nORzVo5de+SBKu\nD7U10ciIo0jdiAklhF01ztaO9AEIE6QLGXw1Ym6J020Mzll2pIg/XcGzmPajDASdCN/TzloVeM+E\nMGX5LDzvcWvxsstOw/u/96Dv/YcPn/I5ZZ593urYtlRdHYIoGzpH7sFxe3J25uphfPONT8IZBqW/\nTVIlkxC2q/gV/fCtVynbp5tIE+XiU9c/gn0npvGu552LP/rinbhp93E3lUrnFHeFWzV3TK3CtNVt\niloYaebgJTk26UWjHD3lj0yRq9vIFKF/sWKoF3/5/HNzaeu1T96SeB/5e+upVfD1O7wqNy2LZ4ok\n0TpguT4dS07rmdOk2zRCvnPSJCGIxUfa6eSHAWwBcAGAgwA+GLYh5/xjnPOLOecXj46Opjwc0Smo\njg/ZCHKNHmWwkV9FlXIzJR/hVn0PnnCaP09eNeRcTRWdIJ1GA0NHVVkti0MnCKfDL6Lrekli4YhL\nt7H///zN+9zXwhC5bsex+ANIBDRJcpgh/cNLtmPDsoHAqb7rG/f5qiiZGNqTktAbTd6IsnFofBZ7\nx6bd1+MzDVz94RvxM6fC1paVg3j8hhEM9savj+g0AnLRJHF+OFNzTZycnncniKNDvThTCoWnOUl3\n8J5v349P37AHJ2ca+OZdjwGQU6mC23vCrcHPatWKz3HhOVSKIUtZWhO86jZ+W6JQTZI2IV/LnmoF\nP3GeSUJAPcs56+4nDu4eU25atoN2HfHKLgN2ZAnndvq3Shd+JQRBxJDKScI5P8w5b3HOLQAfB3Bp\nvt0iOhXV6IlLT1GJMp6StlEEqrBnIJJkqRNJotnXLSUXc4zkkSTcaACXtwnoc8QcL6pss+4TYfCs\nNCiXLLPrqN9oyVe41e7T0n7vO3zs5Ezg8yjOX780t/4QRN7ce2Dc/Xvj8n7sOz6NW/eecKOoalXz\np6O+fHt61PSZl338Jlz1gZ94ZVxDGqeIrc7F1egCMD3vOZjFrXXHo8EA5CjHhyrcKrbNkqoRhSri\nmTei22q6TTfOx2WRVLnKltA8yhZJYv8vPyosLkUaSW3LEXJylA/g6SM989zVeJwy1lMkCUEsPlKl\n2zDG1nLORQ2vFwG4N2p7YvEgmxQXb1qGK86QSqqaBC9EqN6bUuRYFmWMve05Z+OiTcsAhK2QmaEa\ngnFMz7eMVnhl40AM+ElK+4aitDE6ZDuKtq0aSvw9qhU58vCRMOW+k4Vl79rvTSpNbLTVS/q8rtHc\njSgZ8i1Zr1YCkVlJIkHkbc9duwQrhnoyrvb602fEb8/TldBHGNLPrHOZkCojicgBwFs80VVKidIZ\nqTKGmx/xJPK8dJscOqshj0iSqDGQMYYKC46xx6fnQ/boXGRNNNkh4kZ75PhsAUSESjAdS36GqYt4\nwil2wcalsCyOew4ksw8IguguYp0kjLHPA3gqgJWMsf0A3g3gqYyxC2A/k/YA+P0C+0h0EPJY/ztP\nPC0ykkQ3yXTHoQy2SW8tm3p71OHVgVJ+uX3D0lBxQkCcb8SJSR+pZTHDmJxrYqbR8q3YhSFPQpjy\nfxSx6TZKK6PDvc7xkgvfqdWD8pwgiXPoCVlNN5lAyv2jyRtRNuTJlmVxqHO8WgLBJnky8d23PDlz\n3+IiRQLPVs3qMNFhSN/du77uraUxMGwZHYwWONeMTpNzTSwf7HFfe07AgiJJEqS9pqXiCLXLZ3DV\ntu5LTX/ytlH84I+uwrP/+ee+37RwkuQTSeI1fPeBcbz1i3cC8C8QyeO86pxqOQZLtVIJOG0okoQg\nFh+xThLO+Us1b3+ygL4QXYDsHGCKmeNOzFXdEU0aSBbTZMgg3z4t6koq050gkuday8w3Ldyy16yg\nlHCmbFoRrEShEp1uE75fnHCr2pY4ToWxXNNlsiK6WQ11ksS3UXSOOkFkQb47W5wH7tckkSBF6SKo\nExM3DVGNJMkhqpBoL1HfXIUx7QZRkYtXbl2J3ccmA+2XOpIkpgmLc9z32AQev8FL78jiMCgzorqW\n/JuecRZ4qjko7suX+toHjuDktB3JJD9a5Oea+t00pdQf9RsgHwlBLD4KrANCLEqkQYcxoO4r6Rg/\nM4/SvkjRBR/XPHAY/3LNjkxtB1cTZM9I9L6xK6JOU2uW9BlreYgJxgppdS0M2TgQqymmE5GoVZSg\nMeG9k9TGVA3kPPUIRL/CIkZMVorkHGbSSiDKhj+SJHiPJtEkKapiiPqrcXUlaBLSdYSVdGfMHje0\n1W2kbVTqtYqrYQHIUUhFaZJkr24TN0pYPOiMCXPkdzpuCp10uiJ9aq4ZHw0b2q4m6ky2d/y2j7eN\n+t0ILbhqhQXEW4u6xwiCKC/kJCFyRR10dFEdJo6QTPPPkJ1f89lb8Y8/etiwDf3bUYa8mg+r65bJ\neW1YPmB8/lEGpYov3UbR6QiWbubuOcSKumpKGANOJElSJ0nM6zSo5xp2qUyMoJdcvAGPW78U/fUq\nrW8TpUMWmmxZ2SJJ8l7NDkuf0ZXplCFfZOcS9t0xFj4+RH3f9SrzCYAKH0ZR89eFiBy8eNMycHDf\neddziKooJRGRwheetixDs3bDsqNFfp5UfLaPvIijptt4kSTq44+cuASx+OjSJzGx0Jx0hMbkCXWY\nEJ9AN1B66TbpjZO4PbNEAFTVcwpJsdEdITbdxtmJJeij2M4kCkKeIKmpTyq//bGb8PrP3SZ3K5Qw\nY4JpBOniCDprEu2uRRhQnlht+nSbizYtx7fedCXWjfTFb0wQC4ysodDiQU0S9fkVRd4VQ8Kc41HR\nBkRnE6k5wkK+ezEOam6AeqXic5J46TbF3CwPHJwopF2ZSoWh2fL/VruxBDAgPQM033smUWhnV/n5\n5yv7G6qH5H8tnMzVCgvcf0krNRIE0fnQr57IhYPjswDiVoHs201dUZSN57DIhiSEGd3e5+nbjnP8\nCJKskOlyX027GFUuUcVnKCjnoR7vl48cx4/uP+x+GGWDBssiS5EkBv2SUb+7tF/V+es9XHH8AAAg\nAElEQVSXBN5jzP+/SuJJIa1wEyXDv8rOA7+nMmiShP1w1ImuW7GCfmcdixUy2DLYk9BIJ4rmvXqN\n+dJtPD2bDJ3UsMzRzlgITZKaU81OXhjqVk2SKM25LKcs2g37vsLG9kC6jatJUgn0Z8vKofQdJAii\nIyEnCZELkZVqHLaM+sVFdVEGeQi3xhklJoZPWCRLULhVEgGT9tHtb3Gz+Bg7ksRgQ2k7k5U0f/ip\nOFb0ROT3P3crTs01I1OkKhWGh/7mOe5rcY1CVwojCOoVpLsThns9x40u3eY5560J7JPE0GYlE6Ul\nCAC47zFv5bvFg06SJJokSaJOTAhNtxElQFnI9vQ760rCIiajvu96tYKpOa/ymxtJmXN1m5/8yVMB\nAAtQ3AbVCkOL+9NtFpMmiSBLNJDYtyFpyHzi+kdi21bvPzmSRN2nW6N7CIIIh5wkRC4Iw0YectRx\nKaCDoWnHm7QXl26TdOIuE1UCWPa9REQRBwy6FUO26OoZq4acY5hPwJOspPnycsX/MRORH9x32Kgf\nctllL90mhSZJTkap7noI51jT4njGuasDnycx0shcIsqI/NxsaUoArx/pN24rb1mEMAe46GNYlB5F\nknQuUZokdjpm+D5hz/C5puWm99629wQAoKeW7xNZTIgXQpzbiyTxv9eNuELxeafbOP+HlWwOWxhT\nu+FqklRZaNU+giAWD+QkIXJBDDbyoKM6AzxtiIiGwlNWE/cljGaKEFqRjxqVkiEP/FpNkpDDXrVt\nFF94/RPxmis3A3AiMAxF9ZPkZPtLACcb8ZNs7lbOQRqHVD7pNv770GZkwHZGTc+3tE6OxNk2NHkj\nSoZ8S56abaKlPEiGldS4KHqqFTz3/DX4wNWPz6VvYav9oo9hkSRE5xL1/A9Lx/QWE4KctnwAADA+\nY5d27a/bzvkzRvNNhRBjWB7pNnftOxn5ebVSQbPFffZDrUuFW6MWyLJEkriaJCHf11zT/xx8/VVb\nnH74t99x5BQAfSRJUpuJIIjOpzufxETbkAedsEgSd1uDFJ2sfdARZvgcODkjVXTxfybSM4IDp/f3\nhmXeKq3WNuT6FZRKheGJW1agry6iMcy0PGTNAZPxWyfcGtlfiSTfi7hGaVZe1K9mwjGGkyLugT95\n1pmoOVo4m1faBjbnXHu9EkWShKyCEkQ7Ue/JR45Np26LMYYPv/wi/ObFGzP2yk+YWGLYJIR+Zma8\n99v342++fX+7u+EjUnMkJB0zSoxcRF2KcaLFuVZkMytirGzl8JDvq0eb2W4kiXQoWVuom5BT7oKC\n71m+Q+HU0l+3ecVJ8vZfPQfPOGdVYDFqpmFXx1mzpI+ctARBkJOEyAd9JIkfL8XDCbl0X0vbuOGY\nWToT/bFOTO4Xu8bwpL+9Fv9z86PafUQfg+k29hvVCsPWVcORnYitbiMdKy7M92u378dZ7/oe9h2f\ndvaJH9HlbdxoD0NDIFkkiXe8xJokyvb3HBhPtL/MpZuX442/ss19XXVW51qW3kmSxNDOOweeIPJA\n/N7e+bxzANgTZwB42lmjePPTt4XutxCEpfY1La51qOaRermY+OT1j/h0GMpA2HfHGItNx4xyZIt2\nW1b+2jnysfO49eKaqFYZmpbl+11ctCl9OdwyI4+b6nXJo7pNIyTdZrbR0ryrX4zqqVUw2FsrrGIS\nQRCdAzlJiFwwmQyrg45WuFV8lmH9MFAhJUScS0Y4G+549KSzj75fYSWAB3qqvvd1l8M0ctfEVvjy\nrfvRaHHsHZv29c8YVx8m/4mIHEmSWJNE+ntpfx0rBntS9UF3XJHn3bK41smRvLgNTd6IcsEBrBzq\nxTpFe+RPn302/u8zz2xPpxzCNEaaLa51UOYh4k20l7AxjyE8HdMoipKL/3khgppinM8j3aYekzqj\niyQRlQC7FY7gcyBTdRvn/7Dv6+w1w4H3KrrFKB7UayMIYvHS3U9iYsEQQ4086MSl2+jIYwUnMO4p\nr7UOHee4X7ltf6RhFBZtoL67TDO558bVbeIjMIRh6IWqGzQsYUXsp686lCwVBbDP48ZdY/jMDear\nm3KUz9qlfcb7qXAEvxNxzSwevUppQpp0m+/dcxCv+cwtaHZpKDXRfkQqmTrJKoPEQdjPq2lZkRMk\nCiTpZKI0SYDrdhzDP/zgIf8eQrhVu49f1aLZKshJ4o4Vxd981QrDnrFp332epApVR+Had/q049TN\nOvfF1+884Hv/nLVLcMs7noHnPm6tZh+NrQg5arhLvwOCIIwpgelEdAOulofvXSXqwiDeIZcSwDGf\nx60O6XQwGlJpOBNee+VmjA73avsV14LJBFxcJ698plm/XrB9HQBgXpmoy8fTXZ4k5oLqUPmrb5nn\nycuHHuytJTiqrh/+18LwDDN8i1av/5Mv34VrHjziig4SRN6IXP+6MskqIiUhLeqvr2mFRZKUp89E\nOqKr29jf77/9ZKcies69jRTEOCdHkhTx3BZ906XmJqUZo8IuShpPzXuljXu6NJIk6ied5Rkl9tx9\ndCrwvmqHeZ8FqwhaFpciYen5QxCLne58EhMLjhdJ4r0XGGOY/33dilEuJYA1qwMyLYvjJw8ewd9+\n70H9/pp9dh2ZBBBM1RErtuevX+p7f8VQL97wlDMi+xVGmOq/uo3cH9Ph/IKNIwC83F3/upzNkVOz\nwR1T2Aup0lE48NJLT8O333Ql1iztS+8s0+xYldNtcpiUJe3b1LydF52D3U0QWixup5KpkSTlcDjo\nn+0HT85EP17o99KxRD3r5O9cviXue2wi8Lm7j1gccDVJiokkAezxIo9nddyizCWnLwfg19OodauT\nxPlft1CRR3WbQJsRl7FSCYkkiWmTIIjFQ3c+iYkFxxVulavbKNuotoxuEp1PJEm0JsnxqXm8+rO3\n4CM/2+WmPshdiwqxPX/dEt/r1Ut68cGXbMffv2R7YNvA+XJu5ihh8WG+3oTf6b/hiF6vCfHS8P2O\nTMwZtVUEHLa+y/nrl2aSRuUI6o7UpBBq8cnocC/OWWt/p0mMojjRwci+Uf4AURAikqSmPHzSavvk\nSdjva2xqXjtBykOfimgvYd8dg/9+kMe73/v0LfY22pRIp11nc7u6TTFmbIXlU92mxTku27w89HN1\nLAeCkWDdAlMigWSyfI1hUcpR0cu6tGbOvT4WHVlKEET5IScJkRNOuk3UypGoqGIw/c2qSTLc56Vq\nqE09dnLGbV83WJucg/z6xRdtwHpFKBHQlNn1dgo/gNgv5vzFAJ5Uk6QuRVP4+ia91B06TTWXNN+h\n7MAI7YzhsdVrIoxpWZNk+4YRnLV6CACwZeWQcftZ7CeKJCGKwnKMfOEMFeg0khaasN9MK6y6jTIh\nJjqP8HQbf5SG+TPRnzLZanEUFXRRSVGdTUezxd3U0e0blgY+Fw5COQO2W4VboyJJ8qhuY/q+6Iza\nCw6v8l05ou8Igmgn3fkkJhYcYeTIg07AoaDso9VPVYTZ0sC5nVf6J8/yV3MQq6m6FSy5r3bER/gK\nmCnq+ZvaWyxJuk0rmSaJCONV03TkFT+dAbNQ9gLnnoBbViMlTJNErW7zp885Gx+4+vF49nmrEx4h\n3T26EGKAxOJEGPnbN4zgqWeNtrs7WtTbPzT9TWxffJeIgoh61MnPQe2YE1GBzBdJUtDgVGEsF02S\nlsXRW6vgS79/OT76ios1x7H/l6+BvMjTTUQ5PovQAIlqscKCXhLOvX1Ik4QgCHKSELngptvImiTK\nNp6H3tnWfd/b0jWMs0SSwD9Bjqp2c2J6PrB/VHRJkpBQdYzlhoHj2tJ0CoHqNoZ9EmG8wrmiM1qi\nSjNH8Ze/di5efOEGrx3DPsnYaTLy63To9uuVVtfl72b9SD9+8+KNiSv4JL1H1Xx6gsgbEUFVrTC8\n6vLT290dH+L3FRBL5FzrhHW3p99LxxL2rGMwFyeXqbj3hNO+xTNVRYlC1iSxLJ7aYdJyyhRfunk5\n1mgqton+izH5+3/0ZAz0dKmTREQCOdfyVZdvcm2Zvlo1fbvKLeAtiEWl2wTvT7s6GHM/JwhicdOd\nT2JiwfEMWUmTRBll1JUhfSSJ2kqavoicZ71RLnP5+6/Frv/3q/79NduL95KknahbChsrrgWG+PBj\nT+XfiSQxdN6IMN6Wm6YT7E3aOcmrr9ycbkf12MKZlqmdoCbJmauH3b+zGkCaRaj4feCIAtOcjygI\nEUUHZCupWQRhDvCHD09iSFPJSjya7ntsAmevGcaqJelLghPlgikLAaaOY9XR3LR4QH8nLxjzxskX\nffhGrBjswad+95LE7bRi+uim2zjntGyg/alxReF9f/b/q5b04ZZ3PAM7Dp/C0oF6hnb919eLRo3u\nSzDdxovsoUgSgiAokoTIBddFIkeSqE4Sg8mvmNjuOjIZqwofxu2Pnoh0Mqgf2ekXHhaPmAAny7fx\nH9fYEAyWpgtr2o0IMeyYiKY4NOGvYCMfTVsCOIW9kGYF2HZw+VOf0hJIt5EM1az2TxqNFqY4tggi\nbywpXLxMZX8B7zd34MRM4LNlg+ETpFd+6ma89j9vLapbXcFcs9XuLmiJetTFjTkblw0E3lMXB36+\n42iW7kVSrTB3/Llr30lc++CRxG00Wxb2jk1HbiOGJVdMPfFROg9ZEHf5YA8u27IiU3vqNasaRINU\nNOLrlhxJshi+CIIgIiEnCZELJvM+XfpJ2DZ/8N+34zM37knVl4GeKiZmG6F9C5Z984d7R4XVJvKR\nKK85N5v0m4QiB6vbmPXpijNWAgCu3Loy2DkH0/zwIuDwRByzGCm6y+cvq5j9fJI6cMQRSbiVKAp7\nJdSJJCmZkS/EY09MNwKfvf7JWwLvyd2/e/94Ud3qCnYdmWp3F7SEO4SZVpNEfqZuGR3U7QYAeNF/\n3Ijx6QZG+uuFCWxaFscNu8YytTHTsJ1X/RHpM66+mGmoaQcjvqqJGfsZkFe0RlCkXTg6kqbbkCYJ\nQRAelG5D5IJwePg1SfyDjHit6mAw3zYet+45jtekSOHgHLjijBUap0w4ceOhq0mSULcizbFMysuK\nlZJGRNqMjv6eKq7946f4QnrVsNOoNKgkpNIk4YqeTIo2RDsquUaSpEm3IU0SomAsycovW7rNkr46\n+uoVV0BZRvv8okmKMWmjLosmqldSxVtw52/5NJZrKjLJ4+/RyVnMNa2gwz8nGi2Okf70KSCA972c\nuTq8cpobHePqi3XvfS/OTSyA5RUBpV4zkX4c+QhkugUz77FTUGVpgiA6CHKSEPkghFvh85L4MLF5\n5W3mmlb4hhFYTl5+mLGhRrDoQi7DSxea98NEgyXsGHFRCmICdNe+k86xzNky6jfYghEv7TO4LUlL\nJLtuiL8Fn5Mka9up9rFVSUiIkigMLkeSlG+yxcC097+u/Gf5el9emla6sbJoQqvEKU5m4TgW/7/5\nV7airx4U8pRvk0aLY65pobdezGz2ok3L3EiQtIjokKjytmIyLkoAl/Bnmxvquc2ntPHi2vXSbeK1\nYGTsRZr4fQmCWByQr5TIBbEC9NDhydBtKkaDj/dZ2lUGi/snyGrEijZSAsHt9b1LH0liasjaU+lo\nxCrbfY9NAMg+IZLPWatJkrFN432gRJKk9CfodosyVFMdI41yKyjdhigO28loUy3h6B5WFUr30+zm\nyWLeNKWHyo07j7WxJ37CnnV2Sqn3ofhLOEl6NQ4Sez/vpmi2OOYaLfRmqIoSBWPZo/5aJk4SIdy6\niDRJBHkNheo1c6PoIi6mPt3Ge37KX9mq4d6sXSQIogMpoRlFdCIiOmNS0gJRR0CTiAXZMB6bDJbn\nNeqLM9B5lXKUgTBmf51hJN5JMs9WN33w0Cnt+4H9QiYSMgM9fsMwy4RCFYrVa8UkP4CpAfTBHz6E\nzzrht76VHAMB2/CD88B1zjV3nbFU1W0ASrchioNrIkk2r9RoO7SJMAdw3G9zaca0h25HCHgDwMs+\n8cs29kQl/Fnnd8z703XDnP7y+Ds938TUfAt9BUWSMMYyO7SFk8Skus3Ne074Xncj6pnlNhYqDXsL\nchG76NJtpHRf2bH1w7delUMnCYLoNCjdhsgFIUq662i4gJxb3UbVJJFGMnlQE06FxH2BbUypkSOm\nw7Ft1wRXGAIdjEG1dUwdLBUD54A6uGdykkA1WIPbPH/72sTtNgxDaf/12p0AgFdevsntj/x/GtSI\nlLxJ2vRso+WtlpYzMp7oAuzqDPbfwvHQH7IqXyZ0lXjkqIG6RseE8CitJklE2qpOuFWcR+hYKb3/\n8GHbPqgVJB5RUQfGFHiRJOF9rLi/U3ubkQylcMtOwBmam49En1ob5XDS2Vm2cLy9z+krBvHnzz0b\nT9g4gpEuLstMEEQ4FElC5AIHcHB8NnIbdYCMW1HsSRkv7mqShIyPcREsUSN3onQbZVuLm1cBirN5\n1Y+z5M/K5z4+08DNj/gV/f/+6sdj66rhxO0mNfZ0TrMsNmrR06ok2iJP/fufuvnXFElCFIXtHLTv\n/FXDvahWGF7hOB/LQJgotW4O2cUL6gDsCfRLP3YTvnDzo5nbapTU8xo1junEwkVVurD0FHnSOzVv\np+Nu37g0Ux/DqOQQSeJpkoRvU3U1STjWLOkrrFpPGSgqkiS4IMW076v7qN+vXEK9UmF4w1POyFye\nmCCIzoWcJEQucM59Ib8AUs1S5V1aKQdQy1I0SWK2Dwq3Rq+AmaIKynlOgNiEm8TOgaxioGLvt3/t\nHvz7T3b5PhvuS7eydXrCMP+mqu6fwVYMuxzP374Of/rss9I37JDUjj004TkQyUeysPzpl+/C337v\nwXZ3Y0GQc+rXjfTjofc+By+99LS29knGTrcJ/gB0K77yO8cm53F8Kl36ZVmZnm/iF7vH8Odfuydz\nWy117C0J6rj06idtBgDsPDKpjSR50//cAQCYb+mdPj4nyVwTANBTLSZSqpKrJkm4qS3sgabFu94x\nGAgkKSbbRioBHL2XPt2my78EgiCMIScJkQsceuM3cp+YzdMaKHYkiTfZFoaamn6TpF+eJon5ALpl\npb+KjOn52ON7sk6GGZUmMMlYuD5H0b+oPGwdhx1HgrxbeuFWrjV2/vWlT8AfPm1rukYlsphRFEmy\nsHz5tv34yM92xW/YBXDuj8qolU29NURvSeskUd7675v2FtSp9pDnU6C01W2U19ucUrj7Tsz4dGbE\niv6te21djrCqJ/I9MTFjR50UVd0GWFhNkpYV1NHqNtQxOa8sMbVdcbmj022AY5Nz+OF9h9z3Umug\nEQTRlZTMgiI6Ft3YEhqN4TgvtAKh0u7pNTu16TZhzan9iJrEJioBrDm+ySCcJt1GdcgkIuac0i6s\nJBWgE44eV1Mho8lYfLpNuv3ISUIUhVxCu4yE9czkWTE+04jdppPgOfo17t4/nl9jOWIpA9lpywcA\n2AsX//CS7e77asRJmMaK7Gv47C9sp1natNw4Kszul3oOSRDOq6jqNnK6zWKLYsjLKaFetYrBAs1s\nw/5uXv+527z+cH3qH0EQixN6HBC5YHGeIkXE/t+0/G6SvvicLepxYwZmi2u2SK7bGjD81YiWMOzI\nDvML8ZQzR3HaioEEPQsSdU3Smm1JI0karpMku6FYtB8iS+WdkmosEl2AEK0uK7YmiS7dRrOt8uT5\nzI178MJ/v6G0IqVJyXPVuqwVUe7cf9L3WjgLOAfOGB1yHSXqLdEM/Y6D59lXkDBxxdHPSZv2C0jp\nNgbfz44jk12fbgPkpzkW1ibg2R5RtsSZq72FJfE98ZI7mQmCWFjISULkAufm4cNRQ1C4cZSgL/Ab\njbq8U/U1i9hetAkki6pQVyRMDQLGkumoZDWs4rJ70jotolbPdKiaNlnOSy7lVwRZms6qH0Ok4/BE\ntLB0N2DZyq3t7kYoYV3TrvwqbzUtjrv2ncTUfDP/jrWBPH09ZU0TUCsriSpFIppOfO0W57jj0RPu\ndiaRJIJtqzJEUUYgKvBkccrd5UT4RP0kt456ouhldXbliXyGeY2FwXQbFjiWypqlfe7fR0/N2f1B\nqR+fBEEsMOQkIXKBI/mAp9s6j1VCEUniDpyaJtdKA2SgXzk5DFSDxzTaRqxgRZGnUSw7ZfKcwCd1\nkpyYnnf7I8jWn2KtnbRdmzMsjUzkS5jOQTfBHT2mMnNsah6PnZzxvRcn3CpjWlq87OSZdlfW4Br1\nFIWAqeiv+N4tDrzoP250tzO1A15y0Qaj1Io02CVigbEMgsEiouGsNeHV4QZ6PUfSYpigyzZUfpok\n/tfivoq6NepSmpaIFhKp2gRBEAA5SYic0E5mQ8YadwzS7JOHAJ2rSeK83n1sMvD5xmVeegpXuhrl\nzEiWbuN/LQwCkzE4Sf591iE9Lrw0bfvnr09WmnHPsSkAXo55pmiNDPuawEIEKE2490A59QO6kcUW\ntcN58Vo8WWAAvnP3QVzxt9f63tcGkoQ8KLOIVJeJPG/Nsuocqb1S007ES7X/YU6SuqI/UqsWd7eL\nSJJD4+kj0MR5RemmyGmpZf7t5oUvkqQgTZKqQbqNz+Zz7jeLd794LkEQ5pCThMgFDs3E1FR8VBqV\n8ookqTCvROAf/vftgeNGDc5RPUgSSaJuazphOzVr9/tExAqWP90mDw2PfMRqZZ57/hpsWjGASzcv\nN9peRFhslcKn094NnBdbTjFL3nJ/TzE59EQQ+XFS0nlkrtyw61ipxR/D+qaLBgiPJOmOLzJPB57a\n1Ad/+JCr8dRO1HNUowtdEXel/6PDvdr2zlu3BB9/5cWh7eUJcyI6s3xP3sJIlHCr99liiGKQTzGv\nSJKh3hr+4KlnuK/F8yTqap6zdon7t6tJErcTQRCLCnKSELlgGxNm20YEkuDM1eFhqabY6TYMDWfg\ne0xZCeKcK5Mnf0d0q3JimyQ2WVC41ewabd9oR2BMN1qh2+Q5TYiLikhrtzHG7LQmw86KFWJvFSjd\ncd3jZ9s9lrSrYIthsl4W5IliWVfb82Rpf73UaUWhv8mYr2bLykH3766JJMmzLeXe/tdrd+KBgxM5\nHiEd6k+urkR+iBX8hw+f8r3/qitO17bHGMMzz13tjhG1AkuRiOo28sLNu75+Lx46dCpiLz8mdoPv\nHBbBBD1voX7Avi/e9pyz3dcPOvf+Q4fDv6vTVw7iQ799AQBJnJfSbQiCkCAnCZELtjFgNuJFraok\nTdHQ98UJlY1YpohaHbJFaP2fu8KtCawY1TASbca1IcTuTEsPZk+3KS49hcG8Csz4tJ1iJIdkZzGi\nCrV1MqTbLLYUkHYi6wl081Xff2Iaz/nnn+PkdAMXnjbS7u6EEvab1EU9yNvudlLxgO7RllkUmiTK\nr06N/Dhj1I4anGt6CwJnrxnGUG8tsl3RSpGRJBXGYHF/dZvP3bQX/++7Dxi3IRwsURPvxRZJIlPU\nWHjEEWLdf2ImcjtXE4fSbQiC0EBOEiIX0gx1JpPnNIOo0CQJK90X586JSvlJVN0mINyabL+oU8/T\ntogLz8+SWpJEu+MeR6vDC5VNf9x44dtskCHVGRyQjORujiS549GTeNBZ4a4WuLqeHf0vR/fNhD2W\n7lbKynYqi0KTROmWGvkhREvf+sW7ErUrxsikZeaTwGBfV1UmTQiMm+AK1Eb0c7FpkjSkC9ru21Y4\nqGTh1kXmpyIIIoIyW1NEB5Eo3UYUnTEQMj2eQlleaJKEGo5c0SqA30i/a18+Rrh6XroIFR3Cjowy\nfOV28hjUI7+7DO2blDMW1BxxO1/55rQpLeCZnCwmjM80jDR0VEdfOacz3Yn8/bTbIC8S+dSKFLMs\niiu3rgy8F/b77ZavUX6+z0akVpqgu7fLEF2idqGq3JuqkCtgGE3hbFKscKutSaKOw0meIybpNrID\npazOrjyRT3FJf3TEUNEIJ0mzJTRJircbCILoHMhJQuQCj5jObt84op3Im5gDaUwG20nCQtNVOIIe\nHXkiW6sGS/CK10nCYdUIDdcAimnCK4u4MAaTnW7D8cdfugsTjmis+nn6tplxNJAo7SkKAWTWJIky\nTJ0Ph/vSGWnzLQsPHjqFd3793thtyzBZWaz4nSTd+0XI51ZkCkJWxqbmtO8PatIrwn6/zW7RJJFu\nx+/dezBjW+E6Wu0kUAJY+VK1pZ/NfSSFRk25miQBJ7f5dTVJt5GZns/mLOsEtm/00gFf9+QtbeyJ\ndz8KJyVFkhAEIUNOEiIX9o5NuwbR71+1BU/ettIdDD/3mktx01883d02yRiUxs6znIEuypaWm1WP\nEZXznizdJvyYUTDXSRKxke+z7AqnnANfvX1/tnZ0TSeIJBG6BL5IkpR2/lyMbsETtyzHSy/diDf9\nytZU7U/P2UbV529+NHbbQCRJ++cuiwZ5gtPNl12+p3Sr82Uhj3u/0eqOb1K+FlNz2SbHurGinc7Z\nu/efxORcM+DoV8dE3a1q4lAQz3dRwa4I7BLAQW2wJPew2LXMjsuFRlyJJ29biVVL+go5xhMMdZnE\n93L1R36Bv/7WfXjk2FSpq4MRBLGwkJOEyAXZWNm+cQSfe81lWD7YAwBY0lfHas1gaGJspEm34E51\nm7BIDF0IrYxORNAVXc1U3YYbnbOwp0xXAouuApPVaIjWVvE+bORU3YZzjr1j05Eh7MN9dbz/Nx6P\nLaNDodtEkaS8ZndM6TqTlrU4qtvIz8lOm5Al/Z03VZGIDkW+H7Nqa+jv7fbc74+dnMEL/u0GvP1r\n9wQ+U7U5tKWfE1wK0/Lyaag4NoSaUilf6rlmC6/97K24bsdRbRvie6F5t4f4yotwRvzP6y7D3/z6\n+fjkqy4x64t0/336hj04MT2Po6f00W4EQSw+yElCZIIx739jh4YQJnWrveSLLdwaPiniUCbumkgS\ndc906Tb6NuJaqBhEkiyk+Zsp3YaxyL7K34NYIfZrkqRn1XAxq1QAMOM4YExuh0BOexEdIrTIvqwu\n9pH4zq1IMcu8GRmo48+efbb2MzGJWuE42wVjKXSqyoh8O0YJeyZtS9COSJLx6arASYwAACAASURB\nVAau+NtrAQA/vP9QwNGvjp+6qKckk+eeanEmrBi71Osovzx4chY/fuAw3v3N+7RteJok0ef0nhee\nl6GnncWOI5MAgJVDPTFbJueKM1bi5U/chJH+OnpqFbzkog2R28v3H2P2d37VtqA+EkEQi5P2qiYR\nHY+wgZotjrd95W4ACSbVBYmSjE3N29VtAitA4SKOvtUhaWb1uidvxgUbl+H937PL/iUxZYPVbcxO\nRtjLkcKt0mdZp0S2QF34sbIs+DAgcnZqaSJJvOuW7sCiybUjxTlJRInKukFOfDdPzsO498A4bth5\nDK+/aktbw5cXTSSJnG7TQcKtd7zrmaH3R915EC7pr/scIx/92W6ctXoYv3Fh9ASo7Mj3Y9YUKb0m\nSaYmU3Fyxvue5ppWoA+qL0jnG0pyJYotAWxf16Bwq/dapPOFpf0IUyLOSSJ+A138iHI55eiePff8\ntYUdo1JhuOsvn4XeWvT4LA/fvbUKWhZ3Ky4RBEFQJAmRC/tPzOCu/XYJ1zh7L5EmScJ+iGo4J6cb\nxuk2XJGdvXXPCdcQ+q1LTsPzHu8N5tnSbczOx9MkWSDh1tjvK70hGqdJIn+mptsA2YzGIlXqt60e\nEgeJJeiQ635L+B3/ew/e/70H3WdCu1g0kSTS32XWJJEZ6KlGOtCu3LYSL7xgHd76zDMDn12341iR\nXVsQfNE/GR1bugykdjgF5UPqxjv1+9Z9/0n8HsVWt7GjSKIqmIlnedhYI76DuHPqjF9svqwpSI9E\n0N9TjY3Qkp+Vq4b70Gha6KmSk4QgCBtykhC54DfIzIZ8o0CShHaemGhftmV5wHB0V2tijiyHqwdt\nOHNzRh2fTfOTKwarSvJnWedErRbHgZOz2RoJgSH6PPyRJPbfeVW3KZKaswRlok2StoxxJzPprKze\ne6C9ThJZv6KrnSQdUt1G8O7nn4uf/slTI7cZ7qvjQ7/9BLxg+7rAZ1Hi2p2C/J0lSePUtqV5xrTj\nfg9LUxWo96Y2kiTBtagVWt2G4fjUfGQJ4LjHv62PFn9OWb//TqQMp7xx+YD7d7XCMN+yUK+VoGME\nQZQCcpIQqTk07k2sZUMiNjJBESYtIhyfgYWGnXMOPHjolO+1bwVMs8/ocK/dboKupj0vo3SbVC3r\nOTXXxMHxmdDPM6XbMBbpJJBPcd6xOP3XLYVwb+I9knPx6csAAKuc+yKKbp6chyGMz6hV2IXAVwK4\ni51VnXZmIwP1TJUt4qpXdQK+6J/Mwq2a9tsSSeI/pjqGiQWIC53qIzrnQJJLUaRD8MR0AwBwbNKv\ngSM/R+IWPixu5gDpAL9m7pTBMTQyUHf/bloWGi2rUJ0bgiA6C3oaEKk5LuWJp5kLFVHdRm7z1U86\nHQBw8aZlzmdmbem2e+8Lz8erLt+ETdLKQxzaSBKDLjDXSWJ2nKxpJRdsHEFfPTzENJNwK8wjYsTq\nsAiBza61krGBCF5+2SYAwGWbV8RuG7US2a2IS98skZPk367d2caeFIx0mZ+4Jf6e7HTCqol0EpYv\nkiS/tgTt+OUFIkmU1331Kr74+ifiIy+/CEBIdZsET/4iRYqfuMWunDM+rThJfJEk0Ve5xbnRd1sC\nf8GCU2AQkDGyk22uYcHiQJ2cJARBOJBwK5Ea3yqtnP4Rs18SI0i0+08/ehhL++t49ZWbjfZjDNi6\nahhnrxl2SxG7bTr/jwzUcXK6Eah2Y2nO5fz1S3H++qXG/Qb0miR2m6YibmYRGFkNrCX9dZyIqhiR\nKZIkxkkimdHjM/bKXX+P57BJ41BYiBXUSoVh88rBorSHOx5x77faXK71ISli7If3H25jT4pF/h0N\n9pZ/WM/q2I0TZOwEcv1pcGDDsn70VCvYfWzKfqsd6TZx+TYALpOcePp0G/PjFapJ4tyjdyq6SvIZ\nxVWsszg3ipgwTQXuJsoQSSKnax1xSv+KynUEQRCdb2kQhTIx28BsyKDhz/eX021y1CRx/v/QNTvw\nnm/fb7B9cNX+h/cfxpdu2ef1yxVb05OX4J1qyJsuqpuVAM7PmKpVGOaaRRkG0SWAdee42gnDz2pD\nFW2C2VEy8d8DVyZDi8EQFt9duyNJZgu7r8uFfJmXSSHkZSXrb3tiVl9NpJOQnwNZhxyLc1QrDL8m\niYwXJdz6O5+4CW/94p3az9TnIYf9XX/5DZfjX1/6hMD2uolyIidJgeEIoh+DPf4oS111mzBm51tG\n30MZHAYLTRlSjHR9EJHHBEEQsSMMY+xTjLEjjLF7pfeWM8Z+xBjb4fxPT5Uu5cl/9xO88lM3az+T\nI0l8miQxbSq+ikiSRgWoKzvTDduY/rOv3u1uI7otO3Pko1gWz2UVrqaEbapVdMKouNfHrBNZ7Svb\nSRK+rJm5uo1hKWNAY5CmOOaCTctjKvcIFoNTJIgTSdJq77nPNTpfu8IE+Wc0MtATvmEXMT3f2Y6S\nOB2sJAjti7AxLU9u2DmG/73jgPYzXSAJA3DJ6cvxfI0Ar16TxHy8GeorLmoqLGVQfiVsoLCFoZv3\nnHAFyU2OtZhoZ2n4qD4sRocVQRB6TNzwnwHwHOW9PwdwDed8G4BrnNdEFzI+08DNjxzXftb0OUmS\nty0mj0UMSa6uh68EqH08tSwf59z9bNOKAdy1f9yNnslzILdcgyp6O6NIkhwt4FqVRU4mMwm3xnyu\nnqN8vRlYptSZom2dSlx9Y4dgCeBi+lMmxLVvtDmSpBsEPk1YjI642Q53gOX5HLA4B4P/mdfuEsCA\nfV9GjaG6QBCTimGC9SP9xtumJaA7Iju3YoRbVw71GIl7l0GfY6EpqzOipN0iCKINxD6aOec/B6DO\nkl8I4LPO358F8Os594voAEIjSeKq2yQ4RlI7z2hl390o2JO9Y9MAgI/9fHeyAxtw/c5jRtt5wq2G\nkSQZ3UzVSgWHJsJLAGcSbo3RJNk7NhXYXvd3EhZqbsBg9h0FhFsL6k+ZEJOHdmuShKUKdhtt9kW1\nhXZXTsqK/FzI+swSaS0+B0M7NEk06a5RaRW6ifLkXDl+s2Epg7pIkjC4oxUTh7gOi8GBLihDuo2O\nMkS4EARRDtL6r1dzzg86fx8CsDqn/hAdRDNMuNVwjCnSIBCOA7/zxv+eG0mCoD0pxO/yZOVQr9E5\nV1iw70VSZIUAhugSwNPzLV8f1J5kuQJFGztxDiDBIrJ7XcTkod2aJD97uPOroJhw176T7e5CIpL+\nNv/PU8/AyiH/inynO0lOSboqWSOBuCMQesnpy933yhBJ0rJ4pBNf5yQpSxqV6Lfq6JWjG73U3Yh2\naNKtpayRJGV13hAEsfBkDvLj9ogROhozxl7PGLuVMXbr0aOLw2BdLFiSkSorgsdXbzE/RuJIEmUH\n/2od97Vp0o88x0vT45qsKvnOM2MnqzFWQRYjL86RIL6fJf222KRcEjLtURcq9SDOASRYjOk24tHQ\nbk0QtbT1536xpy39KJpOK1uZ9Lf9Z885Gze//em+95ptjlLKyiNj+Tnif7nbDvbtrWWrDJYV9ZiN\nFo/8snVDj4jmbDsikkTRFPHpl8VcZNOxqKwOgyIp6ylnjcwlCKJ7SGtZHWaMrQUA5/8jYRtyzj/G\nOb+Yc37x6OhoysMRZUReJb5t74nE+8fl86bBtVkixGGF4eJzRiyAQWm68ikMxygDTP4k6+WLiyTJ\npEnCgB1HJkM/F/OcHmeSF4gkKbFDwTiSpMwnURDi3jVNMSuKZsvC+euXuK+/dffBiK07F6vDoypM\nqCjPqU6PJKlL55P1ETHUV8PEbAM9UkW1tkSSKAPpqdlG5PhU5igL0TP1PpMvq7jGYRNrHu0j8o7l\nbDQ5V44omoWgrI6hknaLIIg2kNZJ8k0Ar3L+fhWAb+TTHaIoihh8m2ECa7GaJOajUNqoAHEEnR3t\nhsjmcJwkWNzsKGKQvv+xCe3n373nIP73dn11gTTETTay2AzjM43IYwgjUxj3suFUZgMasPtnMk9T\nN1kMIpvi+14x2N5KK/MtC33S6nq576j0tGNCnIU8ftrtTuXKCg/5Oy1P3LLCV3a+HVdHvQ13H5tK\n/F3//dWPz69DGRDjj3qfyWOZiSaJyfmLce+05QMJe9m5lMVJ8vSzV2G5NE6VpFsEQZQAkxLAnwfw\nCwBnMcb2M8ZeA+BvATyTMbYDwDOc10RJ+dIt+3D+u3+Ae/aP59ruL0Oq3piOMclEVtMhr+KfmLYn\n7O7qj4gk0fREDJR5Dpiecya60c0rhyKP/X/++3ackpxeWZ0JawusEHDFGSsB+EPjWxbHDTuPYbbR\nQsv5Lg6OzwAAxqbmffunicJYSOFWk7t499H89W3KjviNtXPyblkcjRb3ra6XxTDPm07zF6QNaT99\nhTeJ7PRIkjx/GrZAKkN/j5xu035NErvqjvl3/QdPPQMvuXhj7HavvHwTXnvl5qTdS0RYJMmBkzPu\n33EptBxm5y+CitYs7UvazY6lLNofn/zdS/C+Xz/ffU3pNgRBCEyq27yUc76Wc17nnG/gnH+Scz7G\nOX8653wb5/wZnHP9bJkoBUK8cE+OOdAAMNxX074fO2mPSIVRSWvmeQ4QTZsaw0btS16TqTNGB6Vj\nmJ1Nv6OjsFBzgPUj0YZZlksh9E5kQ/PnDx/F73zil/jk9Y+416TRyv9ki54Pm6bbzDX91Ro6bNE/\nFcIn1s6J7LwT6VaT9Dq6tdRmp0WSpOUjr7gITz3LTttVtSI6Ddk5n9WhIUoAb14xiKsv2uC0manJ\nVKgLDnc8etKnVxa7v2Gf3/PC8/HOXzs3SddS07I41irOiylnkeJuZ+EpbKjhPOJDH/ZG1S514uoo\nU6So3JeyOG8Igmg/XWoyEj4KeuhbnMeKfkYhDKooz71qPMaV9NStZIW16Y6LGsMsr0v2n6+5zNcX\nE2NY9Mt0gpldkyTuMZD+CELvRA5ZFtEiu45OIk57sczTIMbK3b928sAhO1WsnfPYXUdtLRxZr6N7\nI0k6605M+zWcvWYJXn7ZJgCdH0mSJ3ZaB0OlwvC6J28B0J7oog67DSORx+GBHr8A9Hnv/gGOnJp1\nJ9RbVw2Ft5PgmKruTjdTplOV7dgyOW8Igmgv5CRZRKj2S6NlYWK2od22ZXF86ZZ90e1x/UAXN8Rk\nGYKOTMxFfu45Xmx0goZuJInUE3UrN90mowti2UDd/dukXCDgDdgLFS5dqxYn3CrORf4e3OY43HSb\nvI9rH6dYY6fCmNF31EXzBmNmnNLO7RQUnXRKrG7fuNR9r6egKjD/+Ys9+I+f7iykbRMWk8Og6jyv\n5lvmEQplJN90G+4+L73S9u0Qbu0exPVsWpZ2IeHEVMN1/octNJheDzGOlMlxUDRZFtjyRu4K+UgI\nghCQk2QREPbMf+P/3I4L3/Mj7WfX7zyGP/vq3ZHtWlw/ETUdZNKk25gafsw1FIOI+URF2kbtS14T\nbHnl2nS1V+xjOu/JOqjHlgDO0LYukoT5rrv9/h8/80x9Ayms7oXUJDH6jpRtFkO1m4omzWqhEUe+\n4oyV+NeXPgEAcGq2mOoRf/mN+/CB7z/kChUvNJ12S2V5pghH1x2PnsynM23CJ9yaVXsL3ngmnq9F\n/PTinl3d9GwTNsCuo1PaMbJl8fgx3VC4VSwWlMlxUDRlitiQI3gW0VdAEEQM5CRZxPzgvsOhFQK+\ndvv+2P05uNYAiHMwROmFBI4RSJ9Jtr3OhlGFW7XkJNzaW6vgxRd6OeIm5ywG6fKk26Sn6rTd0jlJ\nOIcokPTM81YH9s3qqCrcBmPM7B7uqvVVM8RkSXcP3/fYOE7/8+/gXV+/t+A+2P8zBjx/+zrUqwzH\np+ejd8pIu5xCnRZJkuW3efaaYQDAdTvaW146M9LglPUZIQukuuOr1P5cs4Vn/uPP8Nkb92Q8TvTn\nac6iLkUylulZKd+jxyaDEawW5+7vTucsuffAOG7ec9xoHBPtdGs6oI4yOSP8WjAl6hhBEG2FnCSL\niLBVHt37cinB8PayGbtxyvDOVso+MStZ8LepK33sbiO99717D/q2yWsAZ4zhg7+5HZecvgzzzRgB\nDmkfWxR0gdJt4iJJMnzJ2kgSqS6MMC7D+pDmCiyUoc1Q7uo77UQY/bp0qnc6zpHP3bS30D6omkdP\n2roy9l7PSjNOZKcgOk2TJAuiWtHPHj7atsidPMg1koR7osRMek8wMdPEjiOTePc378t0nLj7LM15\nfPp3Lw1ofpSNK7etDLxnce4+33TOo5d85BcAzGwkcd0WQyTJiJOCXKpIEhJuJQhCAzlJFgFxg5Fu\ngDdKheFcu/JhWNwGJlPgpJEk3jH8nRjUlEb0Ihq8VclnnWtHNAz06Cv3pOWWPSdw857jxiHiFcYS\npNtkG9WrcZokWdoWaReSgqd83YXRneY+iqNoW8fUmFpE81cAtg6JuHd3HpnEQ4dO+T4/ND67MB1R\nnLC9tUrh30W7Ijo6z0mS/tdZl3RlhPZNJ5LnV2bfdvY1Fc/S+w9OSMfK52Dx93fy41y5bSXe9Cvb\n0nWoQORxVbdo1LK4O65dv/No4HNR1cco3WYRRZJ8+Hcuwh8+7QyfTdZu5GDaMjlvCIJoL+QkIfQV\nYIz2C5ncxuyXbQxKlxN9ztol7t9R6TbveeH5AIA+g0iaIqmwhZv41GPSbbJ8X0IUVrfCLkeShBmH\nZY7UYIwZfUeBFLCC+lMW1OiRT16/2/d6oUxQNWKsWjH7vhIfR2qzXWVpOyzbJtMzRXaSqOW1Own5\nvsl+W3qpr+tG+gH4r3Fe90dcP8Vx/uRZIRpTsQdIt1vR6GwFi3vPupH+nvB9DZ542zcuxehwL170\nhPXpO9khXH7GCvzps88ulTOiSpEkBEFoyHe5nCglcc/8lsVRV5z6JkabnQed4oAJjqFuklbMtEdy\neojj6qoAVCpiMmV2nDSYGAeMscjKL75tM/ant16kJondu0MTs9gy6i+TyDl3SwDrwoyznlfRNpid\nbhO/nbpJxy36J0RdbVZ/SwtlHHvpfJ5Wg+lvKgny+bZbk2QxhOvL52iawlhGeMjfqdri3njWU6ug\nr17xNZqXc/BEjKaPO7YmvA9LNF92iVOpsDh3q3dlfa5sXTWMW97xjExtEOmR79eiq+IRBNE5UCQJ\noZ20meg6hGmSxAu3hh83rm8GYvI+/um3tgf2c0vx6irzgKHCshs9WakytmCT6W2rhiI/z2I0DPXa\nftijpzzhO1m4V1znMCO5zP4EWzem3b0oH6qjoK6U3V2oCZGrSeIcr6jflPysCBPCLhoxCf7aH1zR\nluMnJa9bYK6DnSR5Igu3AnZkXsvi+JdrduDBQxO5OUkeOzkT+bmIjpFX5pPoAJXpcSo/p3SRji2L\nu7/3Ziv8PiyjA4jwI3+/9H0RBCEgJ8kiIsxO0hpQhpokWVaFjRwxyjZJheNe9IQNOHP1kK8dnSaJ\nDGMssM1CU2FwV6liydjHWrW4dJuNyweC7Yk/uPdd5KlJslCGNmPM0Jno36ZMFRyKQHUw9iiaN/L3\nOj5dnPCmG0nivK6wYiI95EyydkWScA5ctGkZtm8cacvx20VcZEOZkX8mWTVDOPxpAhXGsO/ENP7x\nRw/jz796T27Owbj7W3wqR/tc97anxbZbxnmp7HTSjUUW90oAN9qUZkfkw2CvF0pNThKCIATkJFkE\nxD30dVETJkO+apiZHi9LZIKpsSc7bxj86TNRmiSM2QZboek2BttUEqXbZBRuLdAq0FVacJ1T4G51\nirA0gSzGfdFhs6b3yWIzn4WYoRA7HOoLz+p84b9fX1g/XE0S5zaoFKRJ4o8kaU9kQ8viHZVLnzXl\n6oozVgAA7jkwnkd32kKe6TaW5V+wYAyYdkRtD5ycye2+jxuTvFRWry+rh/uM21+oim4mxEWSWJbn\nNGpERJIQ5WfT8kH3b0q3IQhCQE6SRUTYCjbXjO8mxooVEkliOsSkSbeJN/aCn6vldIOaJH4qhoKc\nRVKpLFy6TYxuaya81Jrg9ecceOCgXflEVwIy7URqoQxtxmAYcRX9emqu2dFVOlRECPo7nncOAKCm\n3GDyhGPP2HRh/fDuA6/qRyHpNiXQJDk8MdtRlTGy9vS/X3sZAOCnDwWrinQKeT6nOIKT+rmGPbD3\nVCu5Of3jfIDiOS87vU1uyzLeunFdsriUbhNxgdttSxDx+H47NCsiCMKBHgeLgFjh1rSRJDwsksRQ\nkyTk81ddvsl3jDTGpNoDfySJvx/qfnKqSxEikyZNJqluk7WL6iQ2z/Z1kSTivDgH+uoV9NYqGO6r\na/fPkppSvHCrWbpN3K/puR+6Dr/x4Rvz6VQJmJi1o4NqlQqqFRZwHCzUnCEQSVJYuo3X5iPHpnJv\n34RHxqZwssDUpbLBGOsukdqMtyXnUDRJgFmn8k+9mp/TPza6USxA+Jwk8d+TGIN62lxVTiZWk4Rz\nXPPAEftvi4faKe1ynBLm+DRJKJKEIAiH8oxIROEk0SQxq26Tzokg8ne/ctt+AMHJ7F+94Dx88CWO\n4Cq4NlUmjLCPZQPGTbdxBkP5M8ZYYSvOSRDCewtzrOjPsxgNUSK9Y1NzmG9yrBzqDTluOhZOkyTd\nhF/d5dHj03jg4EQufSoDjzrRI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JUx1paoHRPiSgAP9von0VnuRosHf0v/8JLteO8Lz8vQ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\nhmY3a5drBMzFuIPoxrFdx7r9dMdjPdwGcDWmAMSex6FkQnN95POp181U0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GwXTm5JtpMK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\nkiRJkiQA/gDo+l3dW25aCgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb12c668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "st_result['drawdown'].plot(figsize=(19, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "st_result = st_result[['close','buy', 'sell', 'benchmark', 'pnlplus', 'pnlminus']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "st_result['return'] = st_result['close'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "buy_list = list(st_result.dropna(subset=['buy']).index)\n",
    "sell_list = list(st_result.dropna(subset=['sell']).index)\n",
    "trade_over_list = sorted(list(st_result.dropna(subset=['pnlplus']).index) + list(st_result.dropna(subset=['pnlminus']).index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "order_list = sorted(buy_list + sell_list)\n",
    "sell_dict = {k:'sell' for k in sell_list}\n",
    "buy_dict = {k:'buy' for k in buy_list}\n",
    "directin_dict = dict(buy_dict, **sell_dict)\n",
    "trade_index_pair = [(order_list[order_list.index(trade_over_index)-1], trade_over_index) for trade_over_index in trade_over_list]\n",
    "long_short_trans = {'buy': -1, 'sell':1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "trade_direction = [long_short_trans[directin_dict[direct]] for direct in trade_over_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "max_draw_down_list, return_list = list(), list()\n",
    "for t_index, direct in zip(trade_index_pair, trade_direction):\n",
    "    open_ind, close_ind = t_index\n",
    "    # 获得交易区间的净值曲线\n",
    "    period_net_value = (st_result.loc[open_ind:close_ind]['return'] * direct).add(1)\n",
    "    period_draw_down = (period_net_value / period_net_value.expanding(1).apply(max))-1\n",
    "    # 计算最大回撤\n",
    "    max_draw_down_list.append(abs(period_draw_down.min()))\n",
    "    return_list.append((period_net_value.tolist()[-1] / period_net_value.tolist()[0])-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xafd0eb8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xb393710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.DataFrame(data=[max_draw_down_list, return_list], index=['mm','return']).T.plot.scatter(x='mm',y='return',figsize=(19,7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "open_ind, close_ind = trade_index_pair[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 获得交易区间的净值曲线\n",
    "period_net_value = (st_result.loc[open_ind:close_ind]['return'] * trade_direction[0]).add(1)\n",
    "period_draw_down = (period_net_value / period_net_value.expanding(1).apply(max))-1\n",
    "# 计算最大回撤\n",
    "max_draw_down = abs(period_draw_down.min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.059473531600617857"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_draw_down"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.02199644747027385"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(period_net_value.tolist()[-1] / period_net_value.tolist()[0])-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.059473531600617857"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy</th>\n",
       "      <th>sell</th>\n",
       "      <th>benchmark</th>\n",
       "      <th>pnlplus</th>\n",
       "      <th>pnlminus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   buy  sell  benchmark  pnlplus  pnlminus\n",
       "0  NaN   NaN        NaN      NaN       NaN\n",
       "1  NaN   NaN        NaN      NaN       NaN\n",
       "2  NaN   NaN        NaN      NaN       NaN\n",
       "3  NaN   NaN        NaN      NaN       NaN\n",
       "4  NaN   NaN        NaN      NaN       NaN"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st_result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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